Strong Interannual Variability Research Articles

Spatio-temporal analysis of potential factors explaining fluctuations in population size of Spisula subtruncata in the Dutch North Sea

Bivalves play a key role in coastal ecosystems by supporting food web, modifying habitats, and their economic value for fisheries. Many bivalve species are under pressure, showing large variations in population sizes and distributions, with climate change and human activities considered as important drivers. The Dutch North Sea hosts high densities of bivalve species, dominated by the cut trough shell Spisula subtruncata, with strong interannual variations and a patchy distribution. To explore the causes of this variation, data of an extensive long-term spatial benthic monitoring program (1995-2021) was analysed using a Bayesian spatio-temporal hurdle model. We considered indicators related to human activities, biological processes, climate change and habitat preference as explanatory variables for the observed long-term temporal and spatial variations. Results revealed that medium sediment grain size was key determinant of S. subtruncata occurrence and density. Increasing sea water temperatures during winter and the post-settlement phase positively affected annual population densities, while strong north-westerly winds led to lower densities. These climate change related factors had an overall positive effect on this species in the region. Human activities like shellfish dredging and sand nourishment had no measurable impact. However, shrimp and flatfish beam trawling overlapped with S. subtruncata occurrence and were negatively related to densities, suggesting higher beam trawling intensity in these areas may negatively impacts densities. Overall, the effects were stronger at medium to finer sediments where the highest densities occurred, indicating a strong habitat-dependent effect. Despite identifying multiple drivers, unexplained annual variation suggests other not included factors like predation pressure, also play a role. More detailed studies on the combined effects of climate change-driven environmental stressors and human activities are needed to fully understand the population dynamics. This knowledge is essential for developing more adequate fisheries and coastal management strategies to sustain biodiversity.

Opposite Trends in the Northern Hemisphere Stratosphere Between Mid‐Winter and Early Spring Linked to Surface Temperature Anomalies

AbstractTrends in the coupled stratosphere‐troposphere system during the 1979–2022 period are investigated in the Northern Hemisphere using reanalysis datasets. More upward planetary wave propagation in December is shown to precede the deceleration of the stratospheric polar vortex in January. This deceleration prevents the waves from continuing to propagate upward in February and favors an acceleration of the stratospheric polar vortex in March. This is associated with an increased Northern Hemisphere annular mode in March in the stratosphere and the troposphere. Trends show a moderate significance level because of strong interannual variability. Recent seasons whose anomalies project onto the trends are those for which wave‐1 anomaly constructively interferes with wave‐1 climatology in December, which occurs when there is warming in an area extending from Eastern Canada to Greenland and slight cooling over Eurasia. It shows the potential for predicting the springtime stratospheric polar vortex from wintertime wave‐1 anomalies.

Strengthening of the Equatorial Pacific Upper‐Ocean Circulation Over the Past Three Decades

AbstractThirty years (1993–2022) of concurrent satellite and in‐situ observations show a long‐term strengthening of the equatorial Pacific upper‐ocean circulation. Enhanced southeasterly and cross‐equatorial winds have caused an annual mean, basin‐wide acceleration of the equatorial westward near‐surface currents by ∼20% and an acceleration of poleward flow north (south) of the equator by ∼60% (∼20%). Additional moored velocity data reveal a deepening of the Equatorial Undercurrent (EUC) core at 170°W and significant shoaling at 140°W and 110°W, but no significant changes in EUC core velocity. The strongest subsurface zonal velocity trends are observed above the EUC core in the central to eastern Pacific and occur before and after the seasonal maximum of EUC core velocity, causing enhanced upper‐ocean vertical current shear. Consistent with trends of the 20°C isotherm depth along the equatorial Pacific, a significant basin‐wide steepening of the equatorial thermocline is observed. Both the accelerating equatorial current system and the enhanced thermocline slope are consistent with an observed steepening of the zonal sea surface height gradient due to increased wind‐driven westward mass transport at the surface. During February‐March, both surface and subsurface currents along the equator show eastward velocity trends, in contrast to westward near‐surface current trends during the remainder of the year. The trend reversal is attributed to both a long‐term shift in equatorial Kelvin wave activity and to the impact of strong interannual variability due to El Niño Southern Oscillation and other modes of natural variability on decadal to multidecadal time scales.

Enhancing long-term vegetation monitoring in Australia: a new approach for harmonising the Advanced Very High Resolution Radiometer normalised-difference vegetation (NVDI) with MODIS NDVI

Abstract. Long-term, reliable datasets of satellite-based vegetation condition are essential for understanding terrestrial ecosystem responses to global environmental change, particularly in Australia, which is characterised by diverse ecosystems and strong interannual climate variability. We comprehensively evaluate several existing global Advanced Very High Resolution Radiometer (AVHRR) normalised-difference vegetation index (NDVI) products for their suitability for long-term vegetation monitoring in Australia. Comparisons with the MODIS NDVI highlight significant deficiencies, particularly over densely vegetated regions. Moreover, all the assessed products failed to adequately reproduce the interannual variability in the pre-MODIS era as indicated by Landsat NDVI anomalies. To address these limitations, we propose a new approach to calibrating and harmonising NOAA's Climate Data Record of AVHRR NDVI to the MODIS MCD43A4 NDVI for Australia using a gradient-boosting decision tree ensemble method. Two versions of the datasets are developed, one incorporating climate data in the predictors (“AusENDVI-clim”: Australian Empirical NDVI-climate) and another that is independent of climate data (“AusENDVI-noclim”). These datasets, spanning 1982–2013 at a spatial resolution of 0.05° and with a monthly time step, exhibit strong correlations (r2=0.89–0.94) and low mean errors compared with MODIS MCD43A4 NDVI (mean absolute error (MAE) = 0.014–0.028, RMSE = 0.021–0.046), accurately reproducing seasonal cycles over densely vegetated regions. Furthermore, they closely replicate the interannual variability in vegetation condition in the pre-MODIS era. A reliable method for gap-filling the AusENDVI record is also developed that leverages climate, atmospheric CO2 concentration, and woody-cover fraction predictors. The resulting synthetic NDVI dataset shows excellent agreement with the MODIS MCD43A4 NDVI and the recalibrated AVHRR NDVI time series (r2=0.82–0.95, MAE = 0.016–0.029, RMSE = 0.039–0.041). Finally, we provide a complete 41-year dataset where the gap-filled AusENDVI-clim from January 1982 to February 2000 is joined with the MODIS MCD43A4 NDVI from March 2000 to December 2022. Analysing 40-year per-pixel trends in Australia's annual maximum NDVI revealed increasing values, and shifts in the timing, of the annual peak NDVI across most of the continent, underscoring the dataset's potential to address crucial questions regarding the changing vegetation phenology and its drivers. The AusENDVI dataset can be used for studying Australia's changing vegetation dynamics and downstream impacts on the terrestrial carbon and water cycles, and it provides a reliable foundation for further research into the drivers of vegetation change. AusENDVI is open access and available at https://doi.org/10.5281/zenodo.10802703 (Burton et al., 2024).

Variability of seasonal temperature from 1990 to 2020 within Oum Er Rbia hydraulic basin (Morocco): Study of trends and anomalies

Abstract The fifth report of the Intergovernmental Panel on Climate Change (IPCC) indicates that global temperatures have increased during the 20th century. In Morocco, numerous studies have unveiled that the nation has been contending with the effects of global warming for several decades, attributed to its geographical location. The studies have mainly focused on the evolution of rainfall and the recurrence of droughts. Nevertheless, temperature variations remain less addressed, especially at large spatial scales. This paper aims to study the seasonal temperature variability in the large hydraulic basin of Oum Er Rbia, focusing on its anomalies and trends as well as identifying their impacts on the basin’s territory. Indeed, the large basin of Oum Er Rbia occupies more than 48,.000 km2 and is characterized by an arid to semi-arid climate. Its water resources are important and play an essential role in the country’s socio-economic development. This basin is well-known for its agricultural activity. Although its water and economic potential are significant, the great basin is considered vulnerable to climatic variations, which strongly condition its development. Considering the significance of temperature trends within the framework of global warming, this current study delves into the topic of seasonal temperature variability within the expansive hydraulic basin of Oum Er Rbia. Based on statistical analysis using the temperature anomaly index and the Mann-Kendall trend test, this study reveals that strong interannual variability marked the evolution of seasonal temperatures during the period of 1990-2020, with a remarkable upward trend during the autumn and spring. When the temperature increase, the temperature increases in turn: thus, the negative impacts affect both water resources and the agriculture sector, which suffers from the combined effect of increased evapotranspiration and reduction of irrigation water.

Amaranthaceae Pollen Trends in the Air

Understanding the trends of airborne pollen allergens is of great importance given the high prevalence and socioeconomic impact of pollen-related allergic diseases globally. To study the morphological features of Amaranthaceae pollen, assess its contribution to the aerobiological situation in the city of Karakol and identify periods of increased concentration in order to improve the diagnosis and prevention of pollinosis symptoms in patients. Aerobiological sampling using a Lanzoni pollen trap was carried out from April to October over a three-year period (2015–2017) in Karakol city. Pollen identification and differential counting were performed according to current standard methodology and specially developed guides and atlases. Pollen characteristics of 4 Amaranthaceae species were visualized using scanning electron microscopy (Hitachi) to provide a detailed understanding of the surface structure and ornamentation of pollen grains. The decadal curve of Amaranthaceae pollen concentration in Karakol is unimodal, with often overlapping quantitative characteristics: 6615 (2nd decade of August 2015), 1326 (1st decade of 2016), 444 pollen grains / m3 (1st decade of 2017). At the same time, strong interannual variability of atmospheric pollen levels was observed, depending both on the pollen production of the plants themselves and on meteorological parameters, especially temperature and precipitation, changes in the traditional farming system. The response of summer-flowering Amaranthaceae weeds to climate change was demonstrated, which consists in a decrease in the annual pollen index, which corresponds to the global trend. Peak concentrations of Amaranthaceae pollen many times exceeded clinical threshold values in the air. On the surface of the Bassia scopariapollen exine, the ultrastructure study revealed the smallest (1.5-2.0 μm) granules of sporopollenin or orbicules (Ubisch bodies), which play a role in the spread of allergens. The obtained data are important in terms of increasing public awareness of the dominant pollen of the Amaranthaceae family, optimizing diagnostics, treatment and prevention of pollinosis.

Weakening Indian Ocean carbon uptake in 2015: The role of amplified basin‐wide warming and reduced Indonesian throughflow

AbstractIn 2015, the Indian Ocean exhibits an exceptionally weakened CO2 uptake, highlighting strong interannual variability of ocean carbon sink. By utilizing multiple ocean CO2 partial pressure (pCO2) data and a state‐of‐the‐art ocean biogeochemical model, we show that the 2015 ocean CO2 anomaly is characterized by a basin‐wide amplification of ocean pCO2, differing from ocean pCO2 responses to other Indian Ocean Dipole events (e.g., 1997 and 2019). The distinct ocean pCO2 anomaly is attributed to an amplified warming and an unprecedented weakening Indonesian Throughflow under the influence of co‐occurrence of positive IOD and extreme El Niño in 2015. The amplified warming drives higher ocean pCO2 in the western and central Indian Ocean, while the ITF transports anomalously high ocean pCO2 water from the Pacific Ocean to the southeastern Indian Ocean. This newly identified ocean carbon response provides deeper insights into the Indian Ocean carbon interannual variability.

Environmental control of interannual and seasonal variability in dinoflagellate cyst export flux over 18 years in the Cape Blanc upwelling region (Mauritania)

The increasing threat of anthropogenic environment and climate change amplifies the urgency to investigate the effect of these changes on marine ecosystems. We provide information about the export flux of organic-walled dinoflagellate cysts between 2003 and 2020 in the upwelling ecosystem off Cape Blanc (Mauritania), one of the world’s most productive regions. We compared the cyst export flux with variability in environmental parameters, such as wind speed, wind direction, dust emission, sea surface temperature (SST), SST difference between trap location and open ocean (SSTa), and chlorophyll-a concentration. This information is valuable to determine the ecological signal of dinoflagellate cysts that could be applied in recent and paleo records. The total export production of dinoflagellate cysts fluctuated between 0 - 1.18 x 105 cysts m-2 d-1 for the heterotrophs and 0 - 1.06 x 104 cysts m-2 d-1 for the photo-/mixotrophs. The export productions of both groups were in line with changes in upwelling intensity, which in most years, intensified in spring - summer. Dinoflagellate cyst association was dominated by heterotrophic taxa that formed an average of 94% of the association throughout the sediment trap record. A strong interannual variation in the cyst export fluxes, as well as the association composition was observed in the record. We identified five groups that showed comparable variability in export production with changes in environmental conditions: (1) maximal upwelling; Echinidinium delicatum/granulatum, E. transparantum/zonneveldiae, Echinidinium spp., Trinovantedinium spp., and Protoperidinium latidorsale, (2) combined maximal upwelling and dust input; Archaeperidinium spp., P. americanum, P. stellatum, and P. subinerme, (3) upwelling relaxation; Gymnodinium spp. and L. polyedra, (4) warm surface waters; Bitectatodinium spongium and Protoceratium reticulatum, (5) species with no specific relationship to the studied environmental variables; Brigantedinium spp., E. aculeatum, Impagidinium aculeatum, P. conicum, P. monospinum, Pentapharsodinium dalei, and Spiniferites spp. The sediment trap record documented a gradual shift in the cyst taxa association that co-occurred with the gradual increase of Saharan dust input to the region, notably after 2008. The cyst association contained five photo-/mixotrophic taxa that were formed by potentially toxic dinoflagellates. The latter could cause threats to the socio-economy of coastal communities.

Long‐Term Variability and Tendencies in Mesosphere and Lower Thermosphere Winds From Meteor Radar Observations Over Esrange (67.9°N, 21.1°E)

AbstractLong‐term variabilities of monthly zonal (U) and meridional winds (V) in northern polar mesosphere and lower thermosphere (MLT, ∼80–100 km) are investigated using meteor radar observations during 1999–2022 over Esrange (67.9°N, 21.1°E). The summer (June‐August) mean zonal winds are characterized by westward flow up to ∼88–90 km and eastward flow above this height. The summer mean meridional winds are equatorward with strong jet at ∼85–90 km and it weakens above this height. The U and V exhibit strong interannual variability that varies with altitude and month or season. The responses of U and V anomalies (from 1999 to 2003) to solar cycle (SC), Quasi Biennial Oscillation at 10 and 30 hPa, El Niño‐Southern Oscillation, North Atlantic Oscillation, ozone (O3) and carbon dioxide (CO2) are analyzed using multiple linear regression. From analysis, significant regions of correlations between MLT winds and above potential drivers vary with altitude and month. The positive responses of U and V to SC (up to 15 m/s/100 sfu) indicates the strengthening of eastward winds in mid‐late winter, and poleward winds in late autumn and early winter. The O3 likely intensifies the eastward and poleward winds (∼100 m/s/ppmv) in winter and early spring. The CO2 significantly influence the eastward flow in late winter and summer (above ∼90–95 km) and strengthen the meridional circulation. The significant positive trend in U peaks in summer, late autumn and early winter (∼0.6 m/s/year), the negative trend in V is more prominent in summer above ∼90–95 km.

Interannual Variation of Half-Hourly Extreme Precipitation in Africa: The Assessment of the Warmest Decade (2011–2020) Since the Beginning of Observations

AbstractAfrica is experiencing widespread extreme precipitation. However, the continent remains understudied regarding extreme precipitation variation, particularly at high temporal resolution. This study assessed the changes in spatial distribution, frequency, and intensity of half-hourly violent precipitation (≥ 50 mm/h) in Africa during 2011–2020. The data were sourced from the Integrated MultisatellitE Retrievals for Global Precipitation Measurement (IMERG) program. The results reflect that the 50–60 mm/h precipitation category was the most densely spatially distributed with less-discernable interannual changes. There was a strong interannual variation in the spatial distribution of the 60–70 mm/h and ≥ 70 mm/h precipitation categories. There was a general decrease in the frequency of occurrence of violent precipitation in all regions, except in North Africa (NA). Among the study regions, NA had the broadest precipitation intensity distribution extended to high values and consequently, on average, the most intense violent precipitation, followed by Southern Africa (SA) and Southwest Indian Ocean (SWIO). The regions in the tropics, i.e., West Africa (WA), Central Africa (CA), and East Africa (EA), had a relatively narrow intense violent precipitation distribution. The results further illustrate that the strength of climate variability modes has a strong influence in the distribution, frequency, and intensity of violent precipitation over the continent particularly the ≥ 70 mm/h precipitation category. This study underscores a need for a strengthened capacity in forecasting climate variability modes impacting on Africa, augmentation of continental precipitation observation network, and improved extreme precipitation adaptation infrastructure.

Boreal–Arctic wetland methane emissions modulated by warming and vegetation activity

Wetland methane (CH4) emissions over the Boreal–Arctic region are vulnerable to climate change and linked to climate feedbacks, yet understanding of their long-term dynamics remains uncertain. Here, we upscaled and analysed two decades (2002–2021) of Boreal–Arctic wetland CH4 emissions, representing an unprecedented compilation of eddy covariance and chamber observations. We found a robust increasing trend of CH4 emissions (+8.9%) with strong inter-annual variability. The majority of emission increases occurred in early summer (June and July) and were mainly driven by warming (52.3%) and ecosystem productivity (40.7%). Moreover, a 2 °C temperature anomaly in 2016 led to the highest recorded annual CH4 emissions (22.3 Tg CH4 yr−1) over this region, driven primarily by high emissions over Western Siberian lowlands. However, current-generation models from the Global Carbon Project failed to capture the emission magnitude and trend, and may bias the estimates in future wetland CH4 emission driven by amplified Boreal–Arctic warming and greening.

Multi-elemental stoichiometric ratios of atmospheric wet deposition in Chinese terrestrial ecosystems

Intense human activities have significantly altered the concentrations of atmospheric components that enter ecosystems through wet and dry deposition, thereby affecting elemental cycles. However, atmospheric wet deposition multi-elemental stoichiometric ratios are poorly understood, hindering systematic exploration of atmospheric deposition effects on ecosystems. Monthly precipitation concentrations of six elements—nitrogen (N), phosphorus (P), sulfur (S), potassium (K), calcium (Ca), and magnesium (Mg)—were measured from 2013 to 2021 by the China Wet Deposition Observation Network (ChinaWD). The multi-elemental stoichiometric ratio of atmospheric wet deposition in Chinese terrestrial ecosystems was N: K: Ca: Mg: S: P = 31: 11: 67: 5.5: 28: 1, and there were differences between vegetation zones. Wet deposition N: S and N: Ca ratios exhibited initially increasing then decreasing inter-annual trends, whereas N: P ratios did not exhibit significant trends, with strong interannual variability. Wet deposition of multi-elements was significantly spatially negatively correlated with soil nutrient elements content (except for N), which indicates that wet deposition could facilitate soil nutrient replenishment, especially for nutrient-poor areas. Wet N deposition and N: P ratios were spatially negatively correlated with ecosystem and soil P densities. Meanwhile, wet deposition N: P ratios were all higher than those of ecosystem components (vegetation, soil, litter, and microorganisms) in different vegetation zones. High input of N deposition may reinforce P limitations in part of the ecosystem. The findings of this study establish a foundation for designing multi-elemental control experiments and exploring the ecological effects of atmospheric deposition.

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.

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.

Efficient coastal inundation early-warning system for low-lying atolls, dealing with lagoon and ocean side inundation in Tarawa, Kiribati

Tarawa is a low-lying atoll in the Gilbert Island group, capital of the Republic of Kiribati and home of nearly 70.000 inhabitants. With limited land area, rapid population growth and urbanization, strong interannual sea level variability induced by ENSO and sea level rise, Tarawa is highly vulnerable to coastal flooding. In this context, Early Warning Systems are a proven cost-effective climate adaptation measure to strengthen community resilience. In virtually enclosed atolls, the water level experienced at the shore is compounded by tides, sea level anomaly, storm surge and the contribution of waves. While wave setup and runup, are the primary components driving inundation along the ocean-facing shorelines, sea level anomaly, wind setup and wave pumping through the atoll rim contributes more inside lagoons. In this paper we present an efficient process-based approach to forecast flooding events along both, the ocean and lagoon coasts of atoll islands. With the intention of being highly scalable to other island countries, the system has been designed as a lightweight and accurate tool, that provides actionable and user-friendly water level predictions 7 days in advance. Publicly available global forecast products are ingested by a high-resolution wave model and tailor-made metamodels to translate ocean forcings to water levels at the shore. In absence of a comprehensive topography dataset, extreme value distributions of 27-year hourly water levels were evaluated every 500 m along the coast to define and communicate different levels of warnings according to the recurrence interval of the forecasted event. The long-term wave climate, nearshore wave transformation, and water levels produced under this work increase Tarawa's risk knowledge and support informed investments and future development strategies. While this system will significantly enhance ocean services in Kiribati, improving baseline data still remains a critical need for government and communities to support informed decision making to better cope with increased coastal hazards.

Expressive fluxes over Amazon floodplain revealed by 2D hydrodynamic modelling

Water fluxes in the Amazon River floodplain affect hydrodynamic and ecological processes from local to global scales, but they remain poorly understood due to difficult accessibility and limited data. We characterized the hydrodynamics of eight floodplain units of the central Amazon River (40000 km2) using the 2D hydraulic model HEC-RAS. High resolution modelling (∼400 m) improved the representation of river and floodplain discharge, water surface elevation (77 cm accuracy) and flood extent (∼80% - high water period, ∼52% - low water period) compared to past modelling studies. Our results show that floodplain flows during floods are very intense with upstream inflow and downstream outflow of the floodplain units. These gross flows are much larger than the net flows, with values of up to 20% of the Amazon River discharge and residence time around 6 days during floods (several months during low water period). Water extent did not show strong interannual variability during floods as the volume stored in the floodplain did, possibly due to topographic constraints. Significant hysteresis in flood extent and volume, and active and storage zones on the floodplain highlight the complexity of floodplain hydrodynamics. Extreme floods strongly impacted the onset and duration of the flood by up to one month and, consequently on duration of high water renewal period with the river. Our characterization is important to assess the effects of extreme floods on riverine communities, understand nutrient and sediment variations in the floodplain, and characterize the export of water, sediment, and carbon flux to the ocean from the world's largest hydrological system.

Supraglacial Lake Evolution over Northeast Greenland Using Deep Learning Methods

Supraglacial lakes in Greenland are highly dynamic hydrological features in which glacial meltwater cumulates, allowing for the loss and transport of freshwater from a glacial surface to the ocean or a nearby waterbody. Standard supraglacial lake monitoring techniques, specifically image segmentation, rely heavily on a series of region-dependent thresholds, limiting the adaptability of the algorithm to different illumination and surface variations, while being susceptible to the inclusion of false positives such as shadows. In this study, a supraglacial lake segmentation algorithm is developed for Sentinel-2 images based on a deep learning architecture (U-Net) to evaluate the suitability of artificial intelligence techniques in this domain. Additionally, a deep learning-based cloud segmentation tool developed specifically for polar regions is implemented in the processing chain to remove cloudy imagery from the analysis. Using this technique, a time series of supraglacial lake development is created for the 2016 to 2022 melt seasons over Nioghalvfjerdsbræ (79°N Glacier) and Zachariæ Isstrøm in Northeast Greenland, an area that covers 26,302 km2 and represents roughly 10% of the Northeast Greenland Ice Stream. The total lake area was found to have a strong interannual variability, with the largest peak lake area of 380 km2 in 2019 and the smallest peak lake area of 67 km2 in 2018. These results were then compared against an algorithm based on a thresholding technique to evaluate the agreement of the methodologies. The deep learning-based time series shows a similar trend to that produced by a previously published thresholding technique, while being smoother and more encompassing of meltwater in higher-melt periods. Additionally, while not completely eliminating them, the deep learning model significantly reduces the inclusion of shadows as false positives. Overall, the use of deep learning on multispectral images for the purpose of supraglacial lake segmentation proves to be advantageous.

Heading for a fall: The fate of old wind-thrown beech trees (Fagus sylvatica) is detectable in their growth pattern

Common beech (Fagus sylvatica) is one of the most important deciduous tree species in European forests. However, climate-change-induced drought may threaten its dominant position. The Sonian Forest close to Brussels (Belgium) is home to some of the largest beech trees in the world. This UNESCO world heritage site is famous for its high density of very large beech trees as a result of its climatic suitability, fertile soil conditions, and past management. Here we utilized tree-ring data from increment cores to investigate the growth of these old and monumental beech trees, evaluating their growth trends, response to past climate, and the effect of mast years on 39 living and 16 recently wind-thrown trees. Our analysis reveals that the sampled trees were generally sensitive to spring and summer droughts but recovered quickly after such an extreme climatic event. The growth trend of living trees has remained high and only shows a slight, statistically insignificant, decline over the past 50 years. Although the overall growth rate remains strong (BAI 50 cm2/year), the past five decades have shown strong inter-annual growth variations due to frequent and more intense droughts combined with an increased frequency of mast years. We also found notable differences in growth patterns between the living trees and those that had recently been wind-thrown. While there were no significant differences between living and wind-thrown trees in response to droughts, heatwaves, or mast years when examining year-to-year growth changes, the wind-thrown trees did exhibit considerably lower overall growth rates and a significant downward trend in growth (BAI −0.57 cm2/year). This difference in growth trends has been apparent since at least the 1980s. Overall, the findings of this study can provide valuable insights for understanding the long-term dynamics of lowland beech forests and their responses to climate change.

Changes in crop failures and their predictions with agroclimatic conditions: Analysis based on earth observations and machine learning over global croplands

In this study, we aim to characterize synchronized global crop failures using remote sensing-based products, analyze their predictability and relationships with agroclimatic conditions using machine learning, and identify trends of the most influential agroclimatic indices revealed by machine learning over global croplands. We found that global synchronous crop failures showed strong interannual variability during 1982 to 2016. The most extreme global synchronous crop failure events occurred over 40% of global croplands in the years 2002 (rice and wheat) and 2012 (maize and soy), which had drier and warmer conditions compared to the normal years. Crop failure events can be accurately predicted using machine learning with agroclimatic indices. Of the four crops for both temperate and tropic regions, soy crop failure is most accurately predicted, with an Area Under the Curve (AUC) score of 0.8991 for the temperate region and 0.7892 for the tropics. The AUC score of maize failure in the temperate region is 0.8760, followed by wheat failure (0.8627) and rice failure (0.8025). In the tropics, the remaining crops performed similarly, with AUC scores of 0.7298 (maize), 0.7313 (rice), and 0.7337 (wheat). The machine learning model revealed that growing degree days, last spring frost, first fall frost, growing season precipitation, and optimal field conditions (represented by soil moisture) are the most influential agroclimatic indices, showing various nonlinear relationships with crop failure probabilities. The most influential agroclimatic indices present significant trends on more than 25% of global croplands, showing increasing growing degree days, earlier last spring frost, later first fall frost, while growing season precipitation and optimal field conditions are increasing. Our findings may inform food security predictions, selections of weather index for crop insurance, and climate adaptations.

Variability and Remote Controls of the Warm‐Water Halo and Taylor Cap at Maud Rise

AbstractThe region of Maud Rise, a seamount in the Weddell Sea, is known for the occurrence of irregular polynya openings during the winter months. Hydrographic observations have shown the presence of a warmer water mass below the mixed layer along the seamount's flanks, commonly termed the warm‐water Halo, surrounding a colder region above the rise, the Taylor Cap. Here we use two observational data sets, an eddy‐permitting reanalysis product and regional high‐resolution simulations, to investigate the interannual variability of the Halo and Taylor Cap for the period 2007–2022. Observations include novel hydrographic profiles obtained in the Maud Rise area in January 2022, during the first SO‐CHIC cruise. It is demonstrated that the temperature of deep waters around Maud Rise exhibits strong interannual variability within the Halo and Taylor Cap, occasionally to such an extent that the two features become indistinguishable. A warming of deep waters by as much as 0.8°C is observed in the Taylor Cap during the years preceding the opening of a polynya in 2016 and 2017, starting in 2011. By analyzing regional simulations, we show that most of the observed variability in the Halo is forced remotely by advection of deep waters from the Weddell Gyre into the region surrounding Maud Rise. Our highest‐resolution simulation indicates that mesoscale eddies subsequently transfer the properties of the Halo's deep waters onto the Taylor Cap. The eddies responsible for such transfer originate in an abrupt retroflection along the inner flank of the Halo.