![The X-11 decomposition of the Niño-3.4 SST time series: (a) original series (dashed) and X-11 interannual trend component (solid); (b) X-11 interannually varying seasonal component; and (c) X-11 irregular component. [Note that the vertical scale in (a)-(c) is different-the same interval of 0.2°C is indicated by the vertical bar at the right of each plot.]](https://www.researchgate.net/profile/Sergio-Pezzulli/publication/235961605/figure/fig2/AS:669038111907851@1536522524555/The-X-11-decomposition-of-the-Nino-34-SST-time-series-a-original-series-dashed-and_Q320.jpg)
![The p values (%) of the fixed seasonality test [in case of independent heteroscedastic irregular terms (see appendix C)], applied to the gridded 2-m air surface temperatures.](https://www.researchgate.net/profile/Sergio-Pezzulli/publication/235961605/figure/fig4/AS:669038111903762@1536522524639/The-p-values-of-the-fixed-seasonality-test-in-case-of-independent-heteroscedastic_Q320.jpg)
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The Variability of Seasonality
Journal of Climate
Abstract and Figures
Seasons are the complex nonlinear response of the physical climate system to regular annual solar forcing. There is no a priori reason why they should remain fixed/invariant from year to year, as is often assumed in climate studies when extracting the seasonal component. The widely used econometric variant of Census Method II Seasonal Adjustment Program (X-11), which allows for year-to-year variations in seasonal shape, is shown here to have some advantages for diagnosing climate variability. The X-11 procedure is applied to the monthly mean Niño-3.4 sea surface temperature (SST) index and global gridded NCEP-NCAR reanalyses of 2-m surface air temperature. The resulting seasonal component shows statistically significant interannual variations over many parts of the globe. By taking these variations in seasonality into account, it is shown that one can define less ambiguous ENSO indices. Furthermore, using the X-11 seasonal adjustment approach, it is shown that the three cold ENSO episodes after 1998 are due to an increase in amplitude of seasonality rather than being three distinct La Niña events. Globally, variations in the seasonal component represent a substantial fraction of the year-to-year variability in monthly mean temperatures. In addition, strong teleconnections can be discerned between the magnitude of seasonal variations across the globe. It might be possible to exploit such relationships to improve the skill of seasonal climate forecasts.
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... To simulate scenarios without MHW in the SST time series, we decomposed the daily SST time series ( ) of each ocean spatial cell using a Census X-11 procedure (Pezzulli et al., 2005;Shiskin, 1967;200 Vantrepotte and Mélin, 2011). With this method, the time series can be decomposed as: ...
... The estimation of ( ) on the trend-adjusted series avoids any confusion with the inter-annual (trend) signal. After the revised estimation of these two components (see the method in Pezzulli et al., 2005;Vantrepotte & Mélin, 2011) Gridded monthly NPP data from 1998 to 2021 were obtained from satellite-derived estimation. ...
Marine heatwaves (MHWs) are becoming longer, more frequent and more intense in recent decades. MHWs have caused large-scale ecological impacts, such as coral bleaching, mass mortality of seagrass, fishes and invertebrates, and shifts in abundance and distribution of marine species. However, the implications of these MHW-induced impacts on marine species for the structure and functioning of marine food webs are not clearly understood. In this study, we use the EcoTroph-Dyn ecosystem modelling approach to examine the impacts of MHWs occurring during the year's warmest month on the trophodynamics of marine ecosystems. EcoTroph-Dyn represents marine ecosystem dynamics at a spatial resolution of 1° longitude by 1° latitude and a temporal resolution of 14 days. We applied the model to simulate changes in trophodynamic processes, energy transfer and ecosystem biomass using daily temperature and monthly net primary production (NPP) that were derived from satellite observation from 1998 to 2021. We compared and contrasted the simulated changes in biomass by trophic levels with results generated from temperature and NPP time series that had been filtered to remove MHWs. Our results show a significant decline in biomass between 1998 and 2021 specifically caused by MHWs. For example, in the Northeast Pacific Ocean, our model simulated a specific MHW decline in biomass of 8.7 % ± 1.0 (standard error) in the region from 2013 to 2016. Overall, MHW-induced biomass declines are more pronounced in the northern hemisphere and Pacific Ocean. Moreover, the MHW-induced declines in high trophic level biomass were larger than lower trophic levels and lasted longer post-MHW. Finally, this study highlights the need to integrate MHWs into modelling the effects of climate change on marine ecosystems. It shows that the EcoTroph approach, and especially its new dynamic version, provides a framework to understand more comprehensively the implications of climate change for marine ecosystem structure and functioning.
... This agrees with Abrahamczyk et al. (2011) who reported rainfall, temperature, and day length as the flowering cues of tropical plant species. Seasonal climatic variability has been reported by several authors (Akoun, 2000;Von Holle et al. 2010;Scaven & Rafferty 2013) and according to Pezzulli et al. (2005) it is the normal outcome of the yearly rotation of the earth round the sun. ...
... This is in agreement with Agwu et al. (2020) who reported that rainfall is a key determinant of the natural range of Garcinia kola. The result is in agreement with the general consensus in literature (Liu et al. 2018;Zhou et al. 2018;Rodriguez-Garcia et al. 2019) on differences in resource and environmental requirement of different plant genders. ...
Aim of study: The study designed to assess seasonal climatic variation and flowering intensity in G. kola in a humid forest plantation. Area of study: The study was conducted in the mono-plantation of Garcinia kola in the Swamp Forest Research station of the Forestry Research Institute of Nigeria, Onne, Rivers state, Nigeria. The plantation consists of 103 trees at 5×5m spacing. Material and methods: Climatic data were sourced from meteoblue.com. Flowering intensity was determined by the estimation of the total flower production per tree: total number of flower buds per inflorescence was determined by visual counting and then extrapolated for the total number of inflorescences per twig, total number of twigs per branch and total number of branches per tree to determine the average flowering intensity per tree. A total of 9 trees and twenty-five inflorescences per tree, were sampled. Data was analysed using covariance and analysis of variance. Main results: Rainfall, wind speed, and flowering intensity varied significantly (p ≤ 0.05) between seasons; seasonal rainfall variation influence on flowering intensity varied with tree gender. Research highlights: Rainfall is the flowering cue of the plantation; we recommend that farmers target low to moderate rainfall seasons for high fruit and seed yields.
... Then, a time series can be decomposed as X(t) = S(t) + T(t) + R(t), where S corresponds to the seasonal component, T the trend cycle, and R the residual component (Vantrepotte et al., 2011). This decomposition was performed here using Census-X11 algorithm, originally developed by (Pezzulli et al., 2005) for the analysis of sea surface temperature and then applied on ocean color data (Vantrepotte et al., 2011;Vantrepotte and Mélin, 2009). More details on this method can be found in ( Vantrepotte and Mélin, 2009). ...
... First, the time series of surface water volumes was decomposed in three components using Census-X11 method: trend, seasonal and residual components (Pezzulli et al., 2005;Vantrepotte et al., 2011). The analysis revealed a sharp decline in the seasonal cycle amplitude, with a 70 % reduction in magnitude, from 1109 km 3 to 327 km 3 (grey envelop in Fig. 4a). ...
Water resources play a crucial role in the global water cycle and are affected by human activities and climate change. However, the impacts of hydropower infrastructures on the surface water extent and volume cycle are not well known. We used a multi-satellite approach to quantify the surface water storage variations over the 2000–2020 period and relate these variations to climate-induced and anthropogenic factors over the whole basin. Our results highlight that dam operations have strongly modified the water regime of the Mekong River, exhibiting a 55 % decrease in the seasonal cycle amplitude of inundation extent (from 3178 km2 to 1414 km2) and a 70 % decrease in surface water volume (from 1109 km3 to 327 km3) over 2000–2020. In the floodplains of
the Lower Mekong Basin, where rice is cultivated, there has been a decline in water residence time by 30 to 50 days. The recent commissioning of big dams (2010 and 2014) has allowed us to choose 2015 as a turning point year. Results show a trend inversion in rice production, from a rise of 40 % between 2000 and 2014 to a decline of 10 % between 2015 and 2020, and a strong reduction in aquaculture growth, from +730 % between 2000 and 2014, to +53 % between 2015 and 2020. All these results show the negative impact of dams on the Mekong
basin, causing a 70 % decline in surface water volumes, with major repercussions for agriculture and fisheries
over the period 2000–2020. Therefore, new future projects such as the Funan Techo canal in Cambodia, scheduled to start construction at the end of 2024, will particularly affect 1300 km2 of floodplains in the lower Mekong basin, with a reduction in the amount of water received, and other areas will be subjected to flooding. The human, material and economic damage could be catastrophic.
... This is also observed for the relationship between the polar front jet and deep COLs (Fig. 4c). Hence, whilst there are issues in removing the seasonal cycle as a fixed factor (Pezzulli et al., 2005), the relationship between the strength of the subtropical and polar front jets and COLs remains a hypothesis due to its uncertainty, which requires further study. ...
... This weakening is likely due to the pronounced seasonal cycle in the subtropical jet compared to the monthly variations from climatological means (as shown in Fig. S4). Removing the seasonal cycle weakens the signal, posing a limitation in considering the annual cycle as a fixed factor (Pezzulli et al., 2005). This highlights some uncertainty regarding these relationships, suggesting the need for further work to understand the influence of the jets and their seasonal cycle on the COL intensity. ...
Cut-off lows (COLs) exhibit diverse structures and lifecycles, ranging from confined upper-tropospheric systems to deep, multi-level vortex structures. While COL climatologies are well documented, the mechanisms driving their deepening remain unclear. To bridge this gap, a novel track matching algorithm applied to ERA-Interim reanalysis investigates the vertical extent of Southern Hemisphere COLs. Composite analysis based on structure and eddy kinetic energy budget differentiates four COL categories: shallow, deep, weak, and strong, revealing similarities and disparities. Deep, strong COLs concentrate around Australia and the southwestern Pacific, peaking in autumn and spring, while shallow, weak COLs are more common in summer and closer to the Equator. Despite their differences, both contrasting types evolve energetically via anticyclonic Rossby wave breaking. The distinct roles of jet streams in affecting COL types are addressed: intense polar front jets correlate with more deep COLs, whereas stronger subtropical jets relate to fewer shallow COLs. The COL deepening typically occurs in the presence of a robust upstream polar front jet, which enhances ageostrophic flux convergence and baroclinic processes. The subtropical jet positively correlates with COL intensity but weakens when considering the seasonality, suggesting uncertainties in this relationship. Additionally, we highlight the significance of diabatic processes in COL deepening, addressing their misrepresentation in reanalysis and emphasizing the need for more observational and modelling studies to refine the energetic framework.
... The geometric mean was applied, which is less sensitive to extreme values, meaning that outliers or a small number of Chl-a sat and R rs (λ) samples may have a significantly smaller impact on the results of the time series analysis. The monthly Chl-a sat time series was decomposed on a pixel-by-pixel basis using the Census X11 method (Pezzulli et al., 2005). As described in detail in Vantrepotte and Mélin (2011), this iterative analysis involves the successive application of bandpass filters to decompose the time series into three additive components: seasonal, irregular (sub-annual), and interannual variability. ...
Chlorophyll-a (Chl-a) concentration is a key climate variable, as its variability is associated with meteorological and oceanographic processes. This study analyzed 25 years (1998–2022) of Chl-a data from the European Space Agency (ESA) Ocean Colour Climate Change Initiative (OC-CCI) multisensor archive for the South Brazil Bight, Southwestern Atlantic. Temporal variability and trends were assessed using the Census X11 method, Mann-Kendall, and Sens’ slope tests. The ESA OC-CCI data highlight reliable regional performance, although Chl-a concentrations above 10 mg.m ⁻³ were underestimated. Temporal analyses showed the lowest Chl-a variability (29%) in open ocean waters, with 81% of the variability attributed to seasonal dynamics influenced by the South Atlantic Subtropical Gyre (SASG). A negative Chl-a trend of −11.0% was observed over the 25-year period, attributed to the expansion of the oligotrophic area of the SASG. In the shelf areas southwest of São Sebastião Island, Chl-a variability was moderate (34%–39%), with no discernible long-term trend, but significant interannual variability (44%). The Cape Frio upwelling region shows an increasing Chl-a trend (14.5% in the last 25 years), driven by atmospheric circulation affecting local winds. The highest Chl-a variability (74%) occurred along the southern continental shelf, associated with seasonal nutrient inputs from the Subtropical Shelf Front, with a Chla-a trend increase of 7.5% in 25 years. These results highlight the dynamic and variable Chl-a responses to environmental forcing across the South Brazil Bight.
Although research has reduced uncertainty in the range and magnitude of aerosol climate effects, it remains unclear to what extent decadal changes in dynamical patterns influence aerosols and their accumulation potential. The present study explored how leading dynamic conditions in the tropics affect aerosol interannual variability over subtropical East Asia each March, when the annual pollutant level is highest. We examined tropical convective activity, regardless of seasonality, and evaluated its time-lagged influence poleward on East Asian seasonal air quality the following year. Nonseasonal atmospheric dynamics in the tropical upper troposphere can be characterized as divergent circulation over the Maritime Continent, which alters planetary circulation to a zonal wave-like pattern. In the 21st century, years of increased convective activity over the Maritime Continent have been observed to strengthen the boreal Hadley cell and shift the East Asian westerly jet stream farther poleward, which clears the air over subtropical East Asia the following March. This precursor mechanism may be evaluated with greater confidence when only seasonal decomposition is considered. Moreover, decadal tendencies were found to influence the tropical leading control of air quality in East Asia. This monsoon-Hadley circulation led to narrower variability in air quality in March across the years, with less interference from decadal dynamics. Although mean-state constraints may indicate that climatological change over time modulates decadal changes in regional and synoptic pollutant levels, the aforementioned findings call into question conventional understandings of the role of aerosols in climate variability.
Graphical Abstract
It is explored how leading dynamic conditions in the tropics limit aerosol interannual variability over subtropical East Asia each March, when the annual pollutant level is highest. Years with stronger convective activity over the Maritime Continent, as evidenced by nonseasonal enhancements in divergent circulation in the upper troposphere, resulted in the boreal Hadley cell strengthening and the midlatitude westerly jet stream shifting poleward over the East Asian sector. The resulting increase to the lower-tropospheric northerly flow may have cleared pollutants from the air the following year. Meanwhile, stronger trade winds generated by stronger Pacific anticyclones supported the decadal nonseasonal tendency of stronger divergent circulation in the upper troposphere across the Asia–Australia sector. During decades without excessive interference from tropical dynamics, the leading adjustment of nonseasonal tropical dynamics was followed by better seasonal air conditions over subtropical East Asia. Conversely, when faced with increasing tropical interference, nonseasonal dynamical adjustments to air conditions were only moderate.
Semi-annual climate oscillations in the Western Hemisphere (20 S–35 N, 150 W–20 E) were studied via empirical orthogonal function (EOF) eigenvector loading patterns and principal component time scores from 1980 to 2023. The spatial loading maximum for 850 hPa zonal wind extended from the north Atlantic to the east Pacific; channeling was evident over the southwestern Caribbean. The eigenvector loading maximum for precipitation reflected an equatorial trough, while the semi-annual SST formed a dipole with loading maxima in upwelling zones off Angola (10 E) and Peru (80 W). Weakened Caribbean trade winds and strengthened tropical convection correlated with a warm Atlantic/cool Pacific pattern (R = 0.46). Wavelet spectral analysis of principal component time scores found a persistent 6-month rhythm disrupted only by major El Nino Southern Oscillation events and anomalous mid-latitude conditions associated with negative-phase Arctic Oscillation. Historical climatologies revealed that 6-month cycles of wind, precipitation, and sea temperature were tightly coupled in the Western Hemisphere by heat surplus in the equatorial ocean diffused by meridional overturning Hadley cells. External forcing emerged in early 2010 when warm anomalies over Canada diverted the subtropical jet, suppressing subtropical trade winds and evaporative cooling and intensifying the equatorial trough across the Western Hemisphere. Climatic trends of increased jet-stream instability suggest that the semi-annual amplitude may grow over time.
Amid unprecedented biodiversity loss and water scarcity, calls for corporate responsibility are becoming louder and have led to emerging non‐financial disclosure frameworks with demanding data needs. While the role of satellite remote sensing (RS) is highly anticipated to address data needs and boost transparency, critical thought on what is feasible and how to strategically integrate its insights for ambitious corporate biodiversity and water disclosure is lagging behind. To address this, we propose applying a systems perspective to represent the complex, multi‐scale interactions between biodiversity, water systems, and corporate operations, and to guide how to integrate RS contributions to analyze the full spectrum of impacts and risks—ranging from direct and concurrent to cascading, cumulative, and emergent. We highlight seven guiding (non‐exhaustive) principles for leveraging satellite RS data to assess corporate biodiversity and water impacts and risks. This process requires an effective system boundary (1) set spatially, temporally, and process‐wise. Within which, biodiversity and water's multi‐dimensionality (2) needs to be addressed to monitor the spatio‐temporal dynamics (3) that characterize ecosystem responses. To attribute risk and impact of detected changes, interactions need to be defined by causality (4) and directionality (5), and ultimately consider compound impacts (6) across commodities, supply chains and portfolios, as well as cross‐system interactions (7), for example, between climate change, water and biodiversity. We review each of these principles and related challenges individually, providing a system theory definition, relevant RS capabilities, and research directions. Addressing these seven principles will be crucial to harness satellite RS's potential for comprehensive biodiversity and water disclosure for strong corporate accountability.
We have extensively investigated for the first time the statistical distributions of atmospheric surface variables for the Mediterranean Sea from a 15-year atmospheric analysis dataset that is used for air-sea fluxes computations. We identify and analyze the Probability Density Functions (PDFs) that closely fit the seasonally detrended surface atmospheric variables for wind components (U, V), wind amplitude, air temperature (T2M), dew point temperature (D2M), and mean sea-level pressure (MSL-P). For wind speed the Weibull distribution is sufficient, confirming previous results. The study reveals for T2M, D2M, MSL-P, and wind anomaly components, a skew-normal PDF is needed. Such distribution properly captures the variance and data asymmetric tails (skewness). However, skewness is slight to moderate for almost all the variables except the D2M. We show for the first time that the PDFs parameters vary largely between different Mediterranean Sea subregions. From the PDFs we map also the extreme values, quantified by the 5% and 95% percentile, over the entire basin.
In this paper, the Copernicus Ocean State Report offers detailed scientific analysis of the ocean under climate change, ocean variability, and ocean extremes in the northeastern Atlantic and adjacent seas. Major results show that the northeastern Atlantic Ocean and adjacent seas have experienced consistent warming, with sea surface temperatures increasing at a rate of 0.25 ± 0.03 °C per decade since 1982, doubling the global average trend. This warming is most pronounced in the Black Sea, Mediterranean Sea, and Baltic Sea. Sea levels have risen significantly over the past 30 years, particularly in the Baltic and Mediterranean seas. Ocean acidification has also increased, with pH decreasing at a rate of −0.017 ± 0.001 units per decade. Marine heatwaves have intensified and expanded, affecting over 60 % of the region in 2022 and 2023. Over the past 16 years, most extreme wind speeds exceeding 22 m s−1 prevailed in the central and subpolar North Atlantic and northern Mediterranean Sea. The region has also seen significant variability in ocean climate indicators and circulation patterns, including increased Atlantic Water transport to the Arctic Ocean through the Fram Strait and notable variations in the Mediterranean Sea's meridional overturning circulation. No major Baltic inflow occurred in winter 2022/23.
The global climate in 2000 was again influenced by the long-running Pacific cold episode (La Niña) that began in mid-1998. Consistent with past cold episodes, enhanced convection occurred across the climatologically convective regions of Indonesia and the western equatorial Pacific, while convection was suppressed in the central Pacific. The La Niña was also associated with a well-defined African easterly jet located north of its climatological mean position and low vertical wind shear in the tropical Atlantic and Caribbean, both of which contributed to an active North Atlantic hurricane season. Precipitation patterns influenced by typical La Niña conditions included 1) above-average rainfall in southeastern Africa, 2) unusually heavy rainfall in northern and central regions of Australia, 3) enhanced precipitation in the tropical Indian Ocean and western tropical Pacific, 4) little rainfall in the central tropical Pacific, 5) below-normal precipitation over equatorial east Africa, and 6) drier-than-normal conditions along the Gulf coast of the United States.
Although no hurricanes made landfall in the United States in 2000, another active North Atlantic hurricane season featured 14 named storms, 8 of which became hurricanes, with 3 growing to major hurricane strength. All of the named storms over the North Atlantic formed during the August–October period with the first hurricane of the season, Hurricane Alberto, notable as the third-longest-lived tropical system since reliable records began in 1945. The primary human loss during the 2000 season occurred in Central America, where Hurricane Gordon killed 19 in Guatemala, and Hurricane Keith killed 19 in Belize and caused $200 million dollars of damage.
Other regional events included 1) record warm January–October temperatures followed by record cold November–December temperatures in the United States, 2) extreme drought and widespread wildfires in the southern and western Unites States, 3) continued long-term drought in the Hawaiian Islands throughout the year with record 24-h rainfall totals in November, 4) deadly storms and flooding in western Europe in October, 5) a summer heat wave and drought in southern Europe, 6) monsoon flooding in parts of Southeast Asia and India, 7) extreme winter conditions in Mongolia, 8) extreme long-term drought in the Middle East and Southwest Asia, and 9) severe flooding in southern Africa.
Global mean temperatures remained much above average in 2000. The average land and ocean temperature was 0.39°C above the 1880–1999 long-term mean, continuing a trend to warmer-than-average temperatures that made the 1990s the warmest decade on record. While the persistence of La Niña conditions in 2000 was associated with somewhat cooler temperatures in the Tropics, temperatures in the extratropics remained near record levels. Land surface temperatures in the high latitudes of the Northern Hemisphere were notably warmer than normal, with annually averaged anomalies greater than 2°C in parts of Alaska, Canada, Asia, and northern Europe.
The half-yearly component in the annual march of mean temperature and geostrophic zonal wind, below 100 mb and between 60° E and 120° E, is described by means of cross sections from pole to pole. We suggest that the second harmonics in the temperature, of opposite phase on the equator and in the subtropics, are linked with the position of the rising branch of the Hadley circulation twice a year near the equator. DOI: 10.1111/j.2153-3490.1970.tb00504.x
