Surface Temperature Variability Research Articles

Harnessing the Power of Graph Representation in Climate Forecasting: Predicting Global Monthly Mean Sea Surface Temperatures and Anomalies

AbstractThe variability of sea surface temperatures (SSTs) is crucial in climate dynamics, influencing marine ecosystems and human activities. This study leverages graph neural networks (GNNs), specifically a GraphSAGE model, to forecast SSTs and their anomalies (SSTAs), focusing on the global scale structure of climatological data. We introduce an improved graph construction technique for SST teleconnection representation. Our results highlight the GraphSAGE model's capability in 1‐month‐ahead global SST and SSTA forecasting, with SST predictions spanning up to 2 years with a recursive approach. Notably, regions with persistent currents exhibited enhanced SSTA predictability, contrasting with equatorial and Antarctic areas. Our GNN outperformed both the persistence model and traditional methods. Additionally, we offer an SST and SSTA graph data set based on ERA5 and a graph generation tool. This GNN case study has shown how the GraphSAGE can be used in SST and SSTA forecasting, and will provide a foundation for further refinements such as adjusting graph construction, optimizing imbalanced regression techniques for extreme SSTAs, and integrating GNNs with other temporal pattern learning methods to improve long‐term predictions.

Sea surface temperature driven modulation of decadal co-variability in mean and extreme precipitation

This study investigates the role that sea surface temperature (SST) variability plays in modulating the relationship between decadal-scale mean precipitation and monthly-scale extreme precipitation using the Australian Community Climate and Earth System Simulator Earth System model (ACCESS ESM1.5) climate model. The model large ensemble successfully reproduces the observed strong co-variability between monthly mean rainfall and wet extreme rainfall, defined as monthly rainfall totals above the 95th percentile. Removing SST variability in the ACCESS ESM1.5 model significantly weakens the co-variability between mean and wet extremes over most of the globe, showing that SSTs play a key role in modulating this co-variability. The study identifies Pacific and Atlantic SST patterns as the main drivers of the decadal scale co-variability in mean and extreme wet precipitation. On the other hand, observations and model results show that co-variability between mean and dry extremes is generally weaker than for wet extremes, with highly regional signals. Model experiments also show that SST variability plays a weaker role in modulating the co-variability between the mean precipitation and dry extremes as compared to wet extremes. These results suggest that stochastic atmospheric variability plays a stronger role in generating dry precipitation extremes compared SST forcing.

Seasonal Reversal of ENSO Impacts on SST in the East China Sea–Kuroshio Region

Abstract Sea surface temperature (SST) variability in the East China Sea–Kuroshio (EK) region has important implications for the surrounding weather, climate, and marine ecology. The year-to-year variations of the EK SST are expectedly linked to El Niño–Southern Oscillation (ENSO), the predominant predictability source of seasonal-to-interannual climate variability. Surprisingly, no significant SST signal is observed in the EK region when focusing on the ENSO autumn–winter season with the persistent and pronounced SST anomalies in the tropical Pacific. We find that a remarkable seasonal reversal appears in the ENSO–EK SST connection, shifting from a negative relationship in autumn [Aug(0)–Oct(0)] to a positive relationship in winter [Dec(0)–Feb(1)]. This reversal is mainly attributed to the seasonally varying ENSO-associated western North Pacific (WNP) atmospheric circulation patterns. During ENSO autumns, the anomalous WNP anticyclone is confined south of 20°N, which is accompanied with cyclonic circulation anomalies in the EK region. The associated anomalous northerly wind tends to enhance the background northerly wind, thereby facilitating the local SST cooling mainly via the wind–evaporation–SST effect. In the subsequent winter, the ENSO-related WNP anticyclonic anomalies intensify and extend toward the EK region. Consequently, the weakened background northerly wind induced by southerly wind anomalies leads to the increase of downward latent and sensible heat flux in the EK region, fostering the local SST warming. The observed seasonal reversal of ENSO impacts can be evidenced by the tropical Pacific pacemaker experiments, emphasizing the importance of seasonally modulated ENSO teleconnection and holding implications for the local SST climate prediction.

Temporal-Spatial Variations Analysis of Surface Temperature in Kalimantan Region for The Period of 2010 - 2020

Surface temperature information is important to study because it affects other climate parameters and has an impact on various sectors. This study aims to analyze the temporal and spatial variations of maximum surface temperature on Kalimantan Region during the period 2010 to 2020. The data used is Surface Maximum Temperature (SMT) in the form of a 0.5o x 0.5o grid from the Climate Prediction Center (CPC) NOAA PCL. The results of the temporal analysis showed that the highest monthly SMT values occurred in May (32.00o C) and September (31.75o C). While the lowest monthly SMT values were found in January (30.88o C) and July (31.40o C). The results of the annual SMT trend analysis show that the surface temperature in the Kalimantan Region has increased at an average rate of 0.03°C per year. This value is higher than the increase in global surface temperature (~0.02°C per year). Based on the results of spatial analysis, it was known that the distribution of SMT on Kalimantan Region tends to be stable in the range of 25o C to 35o C throughout the year. Spatial analysis of SMT in 2011 showed that low values (25o - 31o C) dominated South Kalimantan Province , while high values (33°C - 35°C) dominated West Kalimantan Province. The results of the 2019 SMT spatial analysis revealed a similar pattern to 2011. However, there was a significant increase in temperature compared to 2011, especially in the high SMT values observed in West Kalimantan and East Kalimantan Provinces.

Assessment of the Impact of PM2.5 Air Pollution on River Dynamics: A Case Study of Daqing, China.

This study aims to explore the causal relationship between air pollution and river flow in Daqing City, specifically focusing on PM2.5 particle concentration. During comprehensive five-year research, a progressive decrease in air quality was seen, shown by a rise in the yearly average PM2.5 concentration from 13.4 µg/m³ to 18.7 µg/m³. This work utilizes hydrological modeling to reveal a strong negative association between the rise in PM2.5 concentration and the decline in river flow. The decline observed can be attributed to variations in solar radiation and surface temperature, which are clearly impacted by pollution. Ecological investigations showed that the decrease in river flow led to severe ecological impacts, including higher water temperature and alterations in nitrogen levels. This study emphasizes the crucial need to implement thorough environmental management strategies to successfully reduce the detrimental effects of air pollution on river ecosystems. This study enhances our comprehension of the intricate connection between air pollution and river dynamics, on both a regional scale and within the wider context of the southern hemisphere. It highlights the worldwide significance of safeguarding clean air and water resources.

Rapid decrease of the Labrador Sea’s influence on black spruce ecosystems with distance inland

In eastern Canada, Black spruce (Picea mariana Mill. B.S.P.) grows in a wide variety of climates, from maritime-oceanic conditions near the Labrador Sea, to more continental climates, inland. Along this gradient, timing and provenance of heat and moisture that support growth are uncertain, weakening our capacity to predict the response of boreal ecosystems to climate variability. Here, we measured the stable oxygen isotopic composition of black spruce tree-ring cellulose at three sites in eastern Canada and provide evidence of a rapid decrease of Labrador Sea’s influence on adjacent ecosystems. Our results report a landwards decrease in the oxygen isotope composition of both tree-ring cellulose (δ18OTRC) and precipitation water (δ18Op). We also reveal a rapid landwards decoupling between δ18OTRC variability (1950-2013), maximum temperature and Sea Surface Temperature variations over the Northwest Atlantic. Thus, despite their apparent ecological homogeneity, eastern Canada’s black spruce ecosystems rely on heterogeneous sources of heat and moisture.

Multi-decadal pacemaker simulations with an intermediate-complexity climate model

Abstract. In this paper, we first describe the main features of a new version of the International Centre for Theoretical Physics global atmospheric model (SPEEDY) with improved simulation of surface fluxes and the formulation of a three-layer thermodynamic ocean model (TOM3) suitable to explore the coupled extratropical response to tropical ocean variability. Then, we present results on the atmospheric model climatology, highlighting the impact of the modifications introduced in the model code, and show how important features of interdecadal and interannual variability are simulated in a “pacemaker” coupled ensemble of 70-year runs, where portions of the tropical Indo-Pacific are constrained to follow the observed variability. Despite the very basic representation of variations in greenhouse forcing and heat transport to the deep ocean (below the 300 m domain of the TOM3 model), the coupled ensemble reproduces the variations in surface temperature over land and sea with very good accuracy, confirming the role of the Indo-Pacific as a “pacemaker” for the natural fluctuations of global-mean surface temperatures found in earlier studies. Atmospheric zonal-mean temperature trends over 50 years are also realistically simulated in the extratropical lower troposphere and up to 100 hPa in the tropics. On the interannual scale, sea-surface temperature (SST) variability in sub-tropical and tropical regions not affected by SST relaxation is underestimated (mostly because of the absence of dynamically induced variability), while extratropical SST variability during the cold seasons is comparable to that observed. Atmospheric teleconnection patterns and their connections with SST are reproduced with high fidelity, although with local differences in the amplitude of regional features (such as a larger-than-observed response of extratropical SST to North Atlantic Oscillation variability). The SPEEDY-TOM3 model also reproduces the observed connection between averages of surface heat fluxes over the oceans and land surface air temperature in the wintertime northern extratropics. Overall, as in earlier versions of SPEEDY, the fidelity of the simulations (both in terms of climatological means and variability) is higher near the surface and in the lower troposphere, while the negative impacts of the coarse vertical resolution and simplified parameterizations are mostly felt in the stratosphere. However, the improved simulation of surface heat fluxes and their impact on extratropical SST variability in this model version (obtained at a very modest computational cost) make the SPEEDY-TOM3 model a suitable tool to investigate the coupled response of the extratropical circulation to interannual and inter-decadal changes of tropical SST in ensemble experiments.

Marine heatwaves and cold spells in the Brazil Overshoot show distinct sea surface temperature patterns depending on the forcing

The Brazil Current Overshoot regions feature the strongest sea surface temperature variations over the global ocean but forecast skill for these extreme variations is limited. Here we investigate the drivers of marine heatwaves and cold spells in this region and find that ocean flows and sea surface heat fluxes are the primary drivers. We also find that sea surface temperature extremes driven by air-sea heat fluxes produce consistent changes in sea surface temperature and related atmospheric variables over a wide horizontal area, whereas ocean flow-driven sea surface temperature extremes exhibit low consistency in air variables and limited consistency in the spatial extent of sea variables across most sea surface temperature extreme events. These differing air-sea characteristics associated with extremes driven by different drivers offer potential avenues for improving prediction skills and advancing the understanding of three-dimensional air-sea impacts associated with extreme events.

Analysis of Heat and Associated Health Risks in Delhi, India

Climate change has added significant challenges to nation’s worldwide, particularly in Asian countries due to their heavy reliance on climate-sensitive industries like forestry, fisheries, and tourism, Asian countries struggle economically and are slow to seize development opportunities. It has a significant impact on human health, with extreme heat and air pollution leading to thermal discomfort and health problems for city dwellers. Amplified heat waves, elevated levels of air pollution, and extreme weather occurrences are some of the issues faced by city dwellers. Climate change has aggravated health issues in Delhi, India, that includes respiratory and heat-related illness. The present study explores a link between temperature variations, land surface temperatures, and health outcomes to assess climate change risks with heat as the prime focus area in Delhi. It investigates the relationship between average maximum temperature and mortality and find strong positive correlations. It explores yearly land surface temperature variations and the hospital visits and strong correlation exists with temperature for health outcomes like stroke and diabetes. This study analyzes the impact of temperature variations on specific health conditions. Accordingly, the proposals could be framed through understanding of the relationship between heat and health on vulnerable population.

Enhanced impacts of the North Pacific Victoria mode on the Indian summer monsoon onset in recent decades

AbstractVictoria mode (VM), the second dominant mode of North Pacific sea surface temperature variability, has been identified as one of the important factors influencing the Indian summer monsoon (ISM) onset. The positive phase of the May VM delays the ISM onset by both tropical and extratropical pathways. Here, we found a significant interdecadal enhancement of their relationship since the early 1990s, which is mainly attributed to the structure changes and increased variance of the VM. In recent decades, the VM has shown more significant warm SST anomalies in the tropical central Pacific, which drive the large-scale divergent circulation more effectively. This enhanced divergent circulation leads to low-level divergence and reduced rainfall in the tropical Asian summer monsoon region. The reduced rainfall excites equatorial Rossby wave response and anomalous easterly winds in the northern Indian Ocean, delaying the ISM onset. Besides, the increased variance of the VM after 1992/1993 stimulates a stronger extratropical Rossby wave train. This stationary Rossby wave train induces a stronger cooling to the northwest of India, which weakens the land-sea thermal contrast and leads to the delayed ISM onset. This finding should be taken into account to improve short-term predictions of the monsoon onset.

Multidecadal Variations in the Tropical Western Pacific Driven by Externally‐Forced AMV‐Like Changes

AbstractMultidecadal sea surface temperature (SST) variations in the tropical western Pacific (TWP) have been attributed to nonlinear external forcing and remote influences from the Atlantic Multidecadal Variability (AMV). However, the AMV resulted from both internal variability (IV) and external forcing. Thus, the origins of the TWP SST variations are not well understood. By analyzing observations and model simulations, we show that more than half of the decadal to multidecadal SST variations in TWP during 1920–2020 resulted from external forcing with the forced component correlated with AMV, while the internal component is unrelated to AMV. Furthermore, about 43%–49% of the forced AMV‐like SST variations in TWP result from remote influences of the forced AMV in the Atlantic via atmospheric teleconnection over the North Pacific, with the rest from other remote or local processes.

Intrinsic Mode-Based Network Approach to Examining Multiscale Characteristics of Sea Surface Temperature Variability

Variability of sea surface temperature (SST), characterized by various spatiotemporal scales, is a proxy of climate change. A network analysis combined with empirical mode decomposition is newly presented for examining scale-dependent spatial patterns of SST variability. Our approach is applied to SST anomaly variability in the East/Japan Sea (EJS), consisting of satellite-derived daily datasets of 0.25° × 0.25° resolution from 1981 to 2023. Through the spatial distribution of instantaneous energy in intrinsic modes and features of intrinsic-mode networks, scale-dependent spatiotemporal features are found. The season-specific spatial pattern of energy density is observed only for weekly to semiannual modes, while a persistent high-energy distribution in the tongue-shaped region from East Korea Bay (EKB) to the Sub-Polar Front (SPF) is observed only for annual-to-decadal modes. The seasonality is apparent in the time evolution of energy only for weekly-to-annual modes, with a peak in summer and an increasing trend since the 2010s. Hubs of intrinsic-mode networks are observed in the whole southern area (some northern part) of EJS during the summer (winter), only for monthly to semiannual modes. Regional communities are observed only for weekly to seasonal modes, while there is an inter-basin community with annual-to-biennial modes, incorporating two pathways of East Sea Intermediate Water (ESIW).

Modeling the influence of climate on groundwater flow and heat regime in Brandenburg (Germany)

This study investigates the decades-long evolution of groundwater dynamics and thermal field in the North German Basin beneath Brandenburg (NE Germany) by coupling a distributed hydrologic model with a 3D groundwater model. We found that hydraulic gradients, acting as the main driver of the groundwater flow in the studied basin, are not exclusively influenced by present-day topographic gradients. Instead, structural dip and stratification of rock units and the presence of permeability contrasts and anisotropy are important co-players affecting the flow in deep seated saline aquifers at depths >500 m. In contrast, recharge variability and anthropogenic activities contribute to groundwater dynamics in the shallow (<500 m) freshwater Quaternary aquifers. Recharge fluxes, as derived from the hydrologic model and assigned to the parametrized regional groundwater model, reproduce magnitudes of recorded seasonal groundwater level changes. Nonetheless, observed instances of inter-annual fluctuations and a gradual decline of groundwater levels highlight the need to consider damping of the recharge signal and additional sinks, like pumping, in the model, in order to reconcile long-term groundwater level trends. Seasonal changes in near-surface groundwater temperature and the continuous warming due to conductive heat exchange with the atmosphere are locally enhanced by forced advection, especially in areas of high hydraulic gradients. The main factors controlling the depth of temperature disturbance include the magnitude of surface temperature variations, the subsurface permeability field, and the rate of recharge. Our results demonstrate the maximum depth extent and the response times of the groundwater system subjected to non-linear interactions between local geological variability and climate conditions.

A low-cost and open-source approach for supraglacial debris thickness mapping using UAV-based infrared thermography

Abstract. Debris-covered glaciers exist in many mountain ranges and play an important role in the regional water cycle. However, modelling the surface mass balance, runoff contribution and future evolution of debris-covered glaciers is fraught with uncertainty as accurate observations on small-scale variations in debris thickness and sub-debris ice melt rates are only available for a few locations worldwide. Here we describe a customised low-cost unoccupied aerial vehicle (UAV) for high-resolution thermal imaging of mountain glaciers and present a complete open-source pipeline that facilitates the generation of accurate surface temperature and debris thickness maps from radiometric images. First, a radiometric orthophoto is computed from individual radiometric UAV images using structure-from-motion and multi-view-stereo techniques. User-specific calibration and correction procedures can then be applied to the radiometric orthophoto to account for atmospheric and environmental influences that affect the radiometric measurement. The thermal orthophoto reveals distinct spatial variations in surface temperature across the surveyed debris-covered area. Finally, a high-resolution debris thickness map is derived from the corrected thermal orthophoto using an empirical or inverse surface energy balance model that relates surface temperature to debris thickness and is calibrated against in situ measurements. Our results from a small-scale experiment on the Kanderfirn (also known as Kander Neve) in the Swiss Alps show that the surface temperature and thickness of a relatively thin debris layer (ca. 0–15 cm) can be mapped with high accuracy using an empirical or physical model. On snow and ice surfaces, the mean deviation of the mapped surface temperature from the melting point (∼ 0 ∘C) was 0.6 ± 2.0 ∘C. The root-mean-square error of the modelled debris thickness was 1.3 cm. Through the detailed mapping, typical small-scale debris features and debris thickness patterns become visible, which are not spatially resolved by the thermal infrared sensors of current-generation satellites. The presented approach paves the way for comprehensive high-resolution supraglacial debris thickness mapping and opens up new opportunities for more accurate monitoring and modelling of debris-covered glaciers.

Trends and drivers of CO2 parameters, from 2006 to 2021, at a time-series station in the Eastern Tropical Atlantic (6°S, 10°W)

The seawater fugacity of CO2 (fCO2) has been monitored hourly at an instrumented mooring at 6°S, 10°W since 2006. The mooring is located in the South Equatorial Current and is affected by the equatorial Atlantic cold tongue. This site is characterized by large seasonal sea surface temperature variations (>4°C). The fCO2 is measured by a spectrophotometric sensor deployed at about 1.5 meters deep. Measurements of seawater fCO2, sea surface temperature (SST) and sea surface salinity (SSS) are used to calculate total dissolved inorganic carbon (TCO2) and pH. Total alkalinity (TA) is calculated using an empirical relationship with SSS determined for this region. Satellite chlorophyll-a concentrations at 6°S, 10°W are low (<0.2 mg m-3) but some peaks over 0.8 mg m-3 are sometimes detected in August. Nevertheless, the site is a permanent source of CO2 to the atmosphere, averaging 4.7 ± 2.4 mmol m-2d-1 over 2006-2021. Despite the weakening of the wind, the CO2 flux increases significantly by 0.20 ± 0.05 mmol m-2d-1 yr-1. This suggests that the source of CO2 is increasing in this region. This is explained by seawater fCO2 increasing faster than the atmospheric increase during 2006-2021. Most of the seawater fCO2 increase is driven by the increase of TCO2, followed by SST. The fCO2 increase leads to a pH decrease of -0.0030 ± 0.0004 yr-1. The SST anomalies (SSTA) at 6°S, 10°W are correlated to the Tropical Southern Atlantic (TSA) index and to the Atlantic 3 region (ATL3) index with a correlation coefficient higher than 0.75. The strong positive phase of both ATL3 and TSA, observed towards the end of the time-series, is likely contributing to the strong increase of seawater fCO2.

Prevalent underestimation of tree cooling efficiency attributed to urban intrinsic heterogeneity

As cities worldwide grapple with the escalating challenges of extreme heat events, afforestation can serve as an effective adaptation measure to mitigate heat stress. This study presents a comprehensive nationwide assessment of urban tree-induced cooling effects and provides a more accurate and robust methodology that accounts for the influence of spatial heterogeneity within the complex urban environment. Results reveal that the conventional method for assessing cooling efficiency (TCE) is substantially influenced by urban heterogeneity, in terms of both horizontal and vertical structures. The revised tree cooling efficiency (RTCE), designed to minimize the impacts of other land cover types on surface temperature variations, was proved to be a more accurate estimation. In 362 out of 379 cities across China, TCE tended to underestimate the cooling effects as a result of spatial heterogeneity. The nationwide average disparity between RTCE and TCE was approximately 0.047±0.0145 ℃ per percent (95 % confidence interval). The largest differences were observed among high-rise environments, highlighting the undervalued heat mitigation potential of urban trees in compact and densely populated urban settings. This study emphasizes the considerable potential of urban tree-cooling effects in mitigating heat stress in the face of a warming planet.

UAV-mounted thermal camera and its analysis on urban surface textures

Temperature increase, especially global warming, can be observed depending on various factors which led to several severe environmental problems. Urban areas are the most effected places by this temperature increase. Urban heat concentration, the so-called heat island effect, is high in structural areas. This situation causes human life to be adversely affected. Therefore, constant measurement and analyses are required to assess outdoor thermal comfort and thermal stress in urban areas. Today, unmanned aerial vehicle (UAV) systems are used as a rapid data production technique in Earth observation activities. Thermal cameras integrated into UAV systems can monitor the temperature values in urban areas precisely and constantly. This study focuses on the potential application of a UAV-mounted thermal camera system at a local scale due to its rapid response to surface temperature variables. A thermal camera UAV system to measure the energy fluxes and temperatures from the earth’s surface, which are integral to understanding landscape processes and responses. Thus, UAV thermal sensors were used directly for different land cover types in and around the Faculty of Engineering building of Kocaeli University in Turkey. Derived UAV surface temperatures were compared with simultaneously acquired in situ temperature measurements. Simultaneous terrestrial temperature measurements were obtained by using TFA ScanTemp 410 model surface temperature meter. A high correlation between UAV surface temperatures and terrestrial measurements was utilized by Pearson correlation with a 0.94 coefficient. It was concluded that the UAV-mounted thermal camera system is a promising tool that has increased opportunities to understand surface temperature variability at high spatial and temporal resolution.

What Controls the December Precipitation Deficit over the Southern Tibetan Plateau and the Northern Indian Continent?

Abstract Winter precipitation is critical for glacier growth, snow accumulation, and terrestrial storage on the Tibetan Plateau (TP). However, less attention has been paid to the changes in winter precipitation on the TP. In this study, based on the newly developed high-accuracy precipitation dataset, our diagnosis illustrated a distinct precipitation deficit over the southern TP and northern Indian continent (STNI) in December. Together with the ERA5 reanalysis, CESM1.1 large ensemble experiments, and pacemaker experiments, the dynamic diagnosis revealed that the precipitation deficit was attributed to the decrease in dynamic effects. In particular, the enhanced descending motion, accompanied by the strengthened anticyclone and regional meridional circulation over the STNI, resulted in the precipitation deficit. The changes in circulation system related to the precipitation deficit could be attributed to the Pacific and Indian sea surface temperature (SST) variability. With the negative interdecadal Pacific oscillation (IPO), there were circumglobal alternative geopotential height anomalies and an anomalous anticyclone over the southern TP, and descending motion around the STNI associated with the enhanced Walker circulation over the Indo-Pacific, which exhibited a similar pattern to the precipitation deficit over the STNI in the observations. In addition, the synergistic effect of Pacific and Indian SST variability can improve the simulated precipitation deficit over the STNI relative to the Pacific SST variability alone. These results imply a contribution of the tropical SST variability to the precipitation trends over the STNI in early winter and provide an insight into the understanding of climate warming on the winter climate over the TP.

Seasonal types in homogeneous rainfall regions of the Amazon basin

AbstractDue to its size and geographical features, different average annual rainfall regimes co‐exist in the Amazon basin, with distinct year‐to‐year variability dependent on regions within the basin. In this study, we define and explain the seasonal regional types of annual regimes, that is, years with similar seasonal anomalies. Our work is based on a 205 rain gauge network distributed over five Amazonian countries, spanning a period over 30 years. Using a spectral clustering method, we identified seven sub‐regions within the basin in which annual rainfall regimes are spatially homogenous. For each sub‐domain, we estimated specific parameters that characterize the rainy season (onset and demise dates, sign and duration of rainfall anomalies). Finally, using spectral analysis we identified between two and four ‘seasonal type’ of precipitation in these seven sub‐domains. Most of these seasonal types are in phase with the large‐scale atmospheric circulation, which explains the temporal link with rainfall anomalies. The seasonal types result of the superposition of inter‐annual and intra‐seasonal variability whose factors are then difficult to identify and attribute. Part of the rainfall anomalies characterizing seasonal types is related to the inter‐annual variability of the sea surface temperature in the Atlantic or the Pacific oceans, especially in the northeast and southeast part of the Amazon basin, whereas in other parts, strong intra‐seasonal and local factors have a larger impact. The same sign and duration of anomalies do not concomitantly affect the various regions of the Amazon basin, confirming that one mode of variability does not homogeneously affect precipitation in different parts of the basin.

Effects of protection and temperature variation on temporal stability in a marine reserve network.

Understanding the drivers of ecosystem stability has been a key focus of modern ecology as the impacts of the Anthropocene become more prevalent and extreme. Marine protected areas (MPAs) are tools used globally to promote biodiversity and mediate anthropogenic impacts. However, assessing the stability of natural ecosystems and responses to management actions is inherently challenging due to the complex dynamics of communities with many interdependent taxa. Using a 12-year time series of subtidal community structure in an MPA network in the Channel Islands (United States), we estimated species interaction strength (competition and predation), prey species synchrony, and temporal stability in trophic networks, as well as temporal variation in sea surface temperature to explore the causal drivers of temporal stability at community and metacommunity scales. At the community scale, only trophic networks in MPAs at Santa Rosa Island showed greater temporal stability than reference sites, likely driven by reduced prey synchrony. Across islands, competition was sometimes greater and predation always greater in MPAs compared with reference sites. Increases in interaction strength resulted in lower temporal stability of trophic networks. Although MPAs reduced prey synchrony at the metacommunity scale, reductions were insufficient to stabilize trophic networks. In contrast, temporal variation in sea surface temperature had strong positive direct effects on stability at the regional scale and indirect effects at the local scale through reductions in species interaction strength. Although MPAs can be effective management strategies for protecting certain species or locations, our findings for this MPA network suggest that temperature variation has a stronger influence on metacommunity temporal stability by mediating species interactions and promoting a mosaic of spatiotemporal variation in community structure of trophic networks. By capturing the full spectrum of environmental variation in network planning, MPAs will have the greatest capacity to promote ecosystem stability in response to climate change.