Satellite-observed biological variability in the equatorial Pacific during the 2009–2011 ENSO cycle

The event of 2009–2011 El Niño Southern Oscillation (ENSO) provides an opportunity to gain insight into the biological variability of the equatorial Pacific Ocean for an entire ENSO cycle with satellite and in situ observations. Even though El Niño and La Niña in general led to respectively weakened and enhanced chlorophyll-a concentration and net primary production (NPP) along the equatorial Pacific Ocean during the 2009–2011 ENSO cycle, biological responses were highly disparate along the equator and attributed to different driving mechanisms. In the eastern equatorial Pacific east of 150°E, the El Niño-La Niña biological change was in general small except for the transition period even though sea surface temperature (SST) showed over ∼5 °C drop from El Niño to La Niña. In the central-eastern (170°W–140°W) equatorial Pacific, moderate change of biological activity is attributed to the changes of thermocline driven by the eastward propagating equatorial Kelvin waves and changes of zonal currents and undercurrents. Highest biological response in this ENSO cycle was located in the central (170°E–170°W) and central-western (150°E–170°E) equatorial Pacific with quadruple chlorophyll-a concentration and over ∼400 mg C m⁻² d⁻¹ increase of NPP from El Niño in 2009 to La Niña in 2010. However, spatial pattern of ENSO biological variability as represented with NPP is not exactly the same as chlorophyll-a variability. Wind-driving mixing of nutrients and eastward advection of the oligotrophic warm pool waters are attributed to this significant biological variability in this region.     

Interannual variability of the zonal sea surface slope in the equatorial Atlantic during the 1990s

Altimetry data have proven themselves essential for the early detection, analysis and monitoring of large scale tropical anomalies associated with El Niño in the Pacific. Warm events in the Atlantic are much weaker than in the Pacific and are partially masked by the strong seasonal cycle. Satellite altimetric data permits one to estimate the zonal sea surface slope variations at the equator in the Atlantic with sufficient accuracy for resolving interannual sea surface slope variations. The altimetry-derived slope is here shown to detect Atlantic warm events. For all warm events, anomalies in sea surface slope tend to lead SST. In the mid-1990s’, the equatorial interannual variability is dominated by 17-month period events which exhibit the structure observed in local coupled ocean–atmosphere warm events (zonal wind stress weakening and zonal surface slope relaxation, warm SST, excess precipitation). The frequency of occurrence of these Atlantic warm events is seen to have increased during the mid-1990s.     

Assessing the relationship between solar activity and some large scale climatic phenomena

The nature of the climatic response to solar variability is assessed over a long-time scale. The wavelet analysis applied to paleoclimatic proxy data of large scale atmospheric phenomena (North Atlantic Oscillation, Atlantic Multidecadal Oscillation, Pacific Decadal Oscillation and Southern Oscillation Index) has revealed coherence between the climatic oscillations and the solar phenomena (the cosmogenic isotope ¹⁰Be and the Total Solar Irradiance) preferentially with periods of Schwabe, Hale and Yoshimura–Gleissberg cycles that may reflect a modulation of solar activity.     

Spatio-temporal variability of the wet component of the troposphere – Application to satellite altimetry

Due to the presence of water vapour and cloud liquid water in the atmosphere, the wet component of the troposphere is responsible for a delay in the propagation of the altimeter signals, the Wet Path Delay (WPD). The high space–time variability of the water vapour distribution makes the modelling of WPD difficult, its effect still being one of the main error sources in satellite altimetry applications, e.g. in the estimation of Mean Sea Level (MSL). The understanding and the quantification of the WPD variability on various spatial and temporal scales are the main purposes of this study, in view to improve the MSL error budget. The dominant timescales of WPD variability and its correlation with Sea Level Anomaly (SLA) are examined. In these analyses, the atmospheric reanalysis ERA-Interim model from the European Centre for Medium-Range Weather Forecasts (ECMWF) is used to derive a global dataset of daily grids of WPD, spanning a 28-year period from January 1988 to December 2015. The Seasonal-Trend decomposition procedure based on Loess (STL) is used to extract precise WPD annual and interannual signals. Linear trends have been derived from the interannual time series and the contribution of each STL component was mapped globally, allowing the understanding of the WPD variability in spatial terms. The correlation between SLA and WPD is mapped and decomposed into seasons using monthly mean grids, for a period of 21-years, from January 1993 to December 2013.Aiming at inspecting the sensitivity of the results to the used data set, the WPD temporal analysis is extended to the data set provided by the Special Sensor Microwave Imager (SSM/I) and SSM/I Sounder (SSM/IS) Sensors. The WPD from SSM/I(S) is compared against those from the ERA-Interim and from the National Centers for Environmental Prediction (NCEP).Results show that climate phenomena, especially the El Niño Southern Oscillation (ENSO) are the cause for this high variability, since they affect the water vapour and temperature. The observed trends from ERA-Interim, computed globally and over ocean regions only, allow concluding that WPD is increasing with time by approximately 0.1?mm per year, and the maximum trends are observed for the Pacific North and Indian Oceans. High correlation between WPD and SLA is found over the western tropical Pacific.The comparison between WPD from SSM/I(S) and from ERA-Interim and NCEP, allows concluding that the trends computed using only the SSM/I(S) measurement points are substantially larger.     

Is the North Atlantic Oscillation modulated by solar and lunar cycles? Some evidences from Hurst autocorrelation analysis

Several studies have suggested that the Sun and Moon cycles affect the Earth climatic dynamics. Nevertheless, there is a long-standing controversy whether solar variability and tides can significantly generate climate change, and how this may occur. Spectral analysis of climatic indices has provided only indirect evidences of the effects of solar–tidal periodicities in the Earth climate. This work addresses the issue by considering the dynamics of the daily North Atlantic Oscillation index over the period from 1950 to 2009. In contrast to previous studies, this work proposes that external cycles can be detected in the autocorrelation dynamics rather than in the raw North Atlantic Oscillation index series. Here, the R/S-scaling analysis is used to quantify, via the so-called Hurst exponent, the presence of autocorrelations along the studied years. Fourier analysis scan of the autocorrelation series thus show two prominent spectral components near (±3%) the lunar tidal 4.425 and the solar 11 years cycles. Intermediate spectral components near 6.4, 7.75 and 8.9 years are proposed to be, at least partially, a result of energy capture from internal mechanisms into cycles resulting from the nonlinear resonance of the fundamental solar–tidal cycles. The dominant effect of the solar variability is clarified by showing that in about 70% of the studied period the sunspot number and the Hurst exponent phases are synchronized, indicating that a higher solar activity enhances the North Atlantic Oscillation index predictability.     

Effect of the continental shelf in seasonal oceanographic conditions at the Northern edge of the Eastern Tropical Pacific

The continental shelf in front of Nayarit is located in the northern limit of the tropical Eastern Pacific, characterized by constituting a convergence zone of different masses of water, forming an area of significant hydrographic variability. Based on satellite remote sensing data and reanalysis between 2003 and 2019 of sea surface temperature (SST), wind stress, Ekman velocity, and geostrophic velocity, the contribution of the seasonal cycle to the variability of the study area were analyzed through climatological means, Hovmöhler diagrams, and Empirical Orthogonal Functions. The results show that in the zone in front of Matanchén Bay (21.5 °N) and the adjacent continental shelf, there is a core of warm surface water. The distribution of the SST is explained by the seasonal pattern of meridional/zonal variability in the thermal gradient, where the EOFs show the influence of the annual scale in both modes, with the only difference being that the first describes the meridional gradient as the dominant signal (66.2%), and the second shows the zonal behavior of the thermal gradient (16.6%). The summer weakening of the wind stress and Ekman speed is the product of the irregular shape of the coastline, the extension of the continental shelf, and the divergence of the North American monsoon around 21°N, whereas during the rest of the year an intensification of these parameters prevailed in front of Cabo Corrientes. On the other hand, the intense geostrophic flow in summer does not contribute to the increase in SST on the continental shelf because it diverges around 22.5°N. Likewise, during the winter, the formation of a cyclonic geostrophic gyre located inside the continental shelf, between the coast and the Marías Islands, stands out.     

Atmospheric correction of satellite altimetry observations and sea-level variability in the NE Atlantic

Satellite altimetry provides continuous and spatially regular measurements of the height of the sea surface. Sea level responds to density changes of the water, to mass changes, due to addition or reduction of water mass, and to changes in the atmosphere above it. The present study examines the influence of atmospheric effects on sea-level variability in the North-East Atlantic. The association between the height of the sea surface and the North Atlantic Oscillation (NAO) is investigated by considering different sets of altimetry measurements for which the atmospheric effects have been handled differently. Altimetry data not corrected for atmospheric effects are strongly anti-correlated with the state of the NAO, reflecting the hydrostatic response of sea-level to the NAO pressure dipole. The application of an atmospheric correction to satellite altimetry observations in the NE Atlantic decreases variability of the height time series by more than 70% and reduces the amplitude of the seasonal cycle by ∼5 cm. Altimetry data for which atmospheric effects are removed via an inverse barometer correction show a non-negligible correlation with the NAO index at some locations suggesting further indirect non-hydrostatic influences of the state of the NAO on sea level variability.     

Fronts and thermohaline structure of the Brazil–Malvinas Confluence System

Fronts and thermohaline structure of the Brazil–Malvinas Confluence System (BMCS) are studied from climatic data, “Marathon Exp. Leg.8, 1984” data, and Sea surface temperature (SST) data base “ds277-Reynolds” (1981–2000). The South Atlantic Central Water (SACW) is divided in two main types: tropical (TW) and subtropical water (ST). Water masses, Fronts, Inter-Frontal and Frontal Zones are analysed and classified: (a) the water masses: Tropical Low-Salinity Water, Tropical Surface Water, Tropical Tropospheric Water, Subtropical Low-Salinity Water, Subtropical Surface Water, Subtropical Tropospheric Water. T,S characteristics of intermediate, deep and bottom water defined by different authors are confirmed and completed; (b) the Inter-Frontal Zones: Tropical/Brazil Current Zone, Subtropical Zone and Subantarctic Zone; (c) the Frontal Zones: Subtropical, Subantarctic and Polar, and (d) the Fronts: Subtropical Front of the Brazil Current, Principal Subtropical Front, North Subtropical Front, Subtropical Surface Front, South Subtropical Front, Subantarctic Surface Front, Subantarctic Front and Polar Front. Several stable T–S relationships are found below the friction layer and at the Fronts. The maximum gradient of the oceanographic characteristics occurs at the Brazil Current Front, which can be any of the subtropical Fronts, depending on season. Minimum mean depth of the pycnocline coincides with the Fronts of the BMCS, indicating the paths of low-salinity shelf waters into the open ocean. In the work it is shown how to recover the horizontal and vertical thermohaline structure of waters from satellite data RSMAS SST.     

Study of the influence of solar variability on a regional (Indian) climate: 1901–2007

We use Indian temperature data of more than 100 years to study the influence of solar activity on climate. We study the Sun–climate relationship by averaging solar and climate data at various time scales; decadal, solar activity and solar magnetic cycles. We also consider the minimum and maximum values of sunspot number (SSN) during each solar cycle. This parameter SSN is correlated better with Indian temperature when these data are averaged over solar magnetic polarity epochs (SSN maximum to maximum). Our results indicate that the solar variability may still be contributing to ongoing climate change and suggest for more investigations.     

Different mechanisms controlling interannual phytoplankton variation in the South China Sea and the western North Pacific subtropical gyre: A satellite study

A time series of remotely-sensed chlorophyll a (chl a) in 1997–2010 was evaluated to determine mechanisms of phytoplankton variation in recent decade in the South China Sea (SCS) and the western North Pacific subtropical gyre (WNPSG). Satellite-derived sea surface temperature (SST) and aerosol optical thickness (AOT) were used as proxies for vertical nutrient supply and atmospheric aerosol, respectively. Chl a in the WNPSG was not significantly correlated with SST (r = 0.18, p > 0.05), but was with AOT (r = 0.31, p < 0.05), indicating the chl a was influenced by atmospheric deposition. Chl a in the SCS was negatively correlated with SST (r = −0.60, p < 0.05) and was positively with AOT (r = 0.20, p < 0.05). The correlation between AOT and chl a in the SCS does not reflect a major contribution from atmospheric deposition to chl a; instead, the relationship resulted from concurrence of the peaks of AOT and wind speed, which drive water mixing and nutrient supply. Consequently, chl a in the SCS would be regulated primarily by the nutrient supply from deep waters. Because SST was controlled by the ENSO teleconnection in the SCS, the chl a was coupled with ENSO events. The present study demonstrated that interannual phytoplankton variation could be controlled by different factors even in neighboring oligotrophic regions.     

Doppler utilised Kalman estimation (DUKE) of ionospheric delay for satellite navigation

The ionospheric delay experienced by the satellite navigation signals depends upon the Total Electron Content (TEC) and needs to be corrected. While the single frequency receivers always use parametric models to correct this delay, dual frequency receivers, when suffers a loss of lock of one of its signal, also has to resort to these models. Here, an alternative method, based on Doppler, surrogated by range rate variation, has been attempted to estimate the ionospheric delay using a Kalman filter. GPS data have been used for all visible satellites over four days selected around the equinox and solstice with nominal geomagnetic conditions and estimations done in continuous and calibrated modes. Results of continuous estimation, obtained for a mid latitude station, showed moderate accuracy while it was significantly better for the calibrated mode with no seasonal dependence. Estimations done for station within the extent of equatorial anomaly, has not only resulted in relative deterioration in performance, but also shown seasonal dependence. Compared with estimates of Klobuchar model, the Calibrated estimation showed superior performance, conspicuously in the mid latitude station. However, for the continuous mode, performance was at par with the model at higher latitudes but inferior to it in regions within the extent of the equatorial anomaly.     

On the uncertainties in the measurement of absolute (true) TEC over Indian equatorial and low latitude sectors

The Indian sector encompasses the equatorial and low latitude regions where the ionosphere is highly dynamic and is characterized by the equatorial ionization anomaly (EIA) resulting in large latitudinal electron density gradients causing errors and uncertainties in the estimation of range delays in satellite based navigation systems. The diurnal and seasonal variations of standard deviations in the TEC data measured during the low sunspot period 2004–2005 at 10 different Indian stations located from equator to the anomaly crest region and beyond are examined and presented. The day-to-day variability in TEC is found to be lowest at the equatorial station and increases with latitude up to the crest region of EIA and decreases beyond.     

Decadal variability of tropical Pacific temperature in relation to solar cycles

We use the 8-year long satellite temperature data (2002–2010) from Atmospheric InfraRed Sounder (AIRS) and Atmospheric Microwave Sounding Unit (AMSU) on the Aqua satellite to identify temperature trends in the troposphere and low stratosphere over the Niño 3.4 region of the Tropical Pacific Ocean in the most recent 11-year solar cycle. Employing more extended sea surface temperature (SST) data for five solar cycles (1950–2009) in this region we show that the satellite trends reflect a typical decrease of the sea surface temperature (SST) in the Niño 3.4 region in the declining phase of the solar cycle. The magnitude of the SST decrease depends on the solar cycle and ranges between 0.07 K/yr and 0.27 K/yr for the last five solar cycles.     

Seasonal variation of total electron content at crest of equatorial anomaly station during low solar activity conditions

The variability of total electron content (TEC) over the crest of equatorial anomaly station Bhopal has been studied during the low solar activity period (2005–2006) using global positioning system (GPS) data. Diurnal variation of TEC is studied for different seasons. Interesting features like the winter anomaly, semiannual anomaly and noon bite out in TEC have been reported. GPS derived TEC is then compared with International Reference Ionosphere (IRI) 2001 model and the difference between predictions and observation is being studied. Using the variability index we have also studied the TEC variability for different seasons and also during quiet and disturbed conditions. A higher variability is observed on quiet days as compared to disturbed days during daytime and nighttime hours.     

Analysis of the variability of temperature gradient in the ocean frontal zones based on satellite data

AVHRR MCSST data for the periods 1982–2000 (mean weekly data) were used to calculate mean gradient fields in the ocean for different periods of time. Three-month averaged sea surface temperature gradients (SSTG) and their mean seasonal variations have been studied for 25 points in the large-scale oceanic fronts zones. Major oceanic fronts in the Atlantic and Pacific have been identified and compared in literature. In the North Atlantic and Pacific, the areas under study were the North Polar Front and Subpolar Fronts. In the South Atlantic and Pacific we studied the region of the Antarctic Circumpolar Current (ACC) and the fronts formed by this current, known as the South Polar Front, and the Subantarctic Front. SSTG were also calculated for El Niño (Southeast Pacific) and Benguela Current (Southeast Atlantic).     

Evaluating the predictability of eight Atmospheric-Oceanic signals affecting Iran’s Droughts,employing intelligence based and stochastic methods

The large-scale atmospheric-oceanic phenomena are among the main effective factors in the droughts in the Middle East, especially in Iran. Since these effects are usually delayed, their relevant signals can be useful for predicting droughts. As a result, the provision of a precise prediction of these signals can be efficient in increasing the drought prediction prospect. The current study predicts 8 cases of the most effective oceanic signals on the droughts which have been investigated in Iran. To do so, the problem-solving method with the time series prediction approach is based on the two model types intelligence-based (including multilayer perceptron [MLP] and support vector machine [SVM]) and stochastic (including Autoregressive Integrated Moving Average [ARIMA]) has been used. The model's input for each index included the time lags of the same index itself, which was determined by the autocorrelation function. Based on the evaluation criteria, the results were indicative of the weak predictability of the North Atlantic Oscillation (NAO) and Arctic Oscillation (AO), while the Extreme Eastern Tropical Pacific sea surface temperature (Niño [1 + 2]), East Central Tropical Pacific sea surface temperature (Niño [3 + 4]), and Oceanic Niño Index (ONI) were predicted with very good accuracy, and there is a high overlap between their predictions and observations (95.9 % < R² < 99.3 %). In the extreme events also, the rate of normalized forecasting error for Niño (1 + 2), Niño (3 + 4), and ONI were in the medium (20–30 %), good (10–20 %), and excellent (0–10 %) ranges, respectively. The comparison between the models also indicates a partial superiority of the ARIMA stochastic model over the SVM and MLP models. The overall results of the study are indicative of the applicability of the predictions of the three mentioned indices as the inputs to increase precipitation and drought forecasting prospects in Iran (as well as all regions affected by them); which have the research value for further studies in terms of drought forecasting.     

Seasonal-to-interannual variability of chlorophyll-a bloom timing associated with physical forcing in the Gulf of Cádiz

Seasonal-to-interannual variability of the winter-spring bloom in the Gulf of Cádiz, eastern North Atlantic, has been investigated using chlorophyll-a remote sensing (CHL). These data have been obtained from the GlobColour project; the temporal coverage extends from September 1997 to December 2010. In this study we develop a generic quantitative approach for describing the temporal variability in the shape of the winter-spring bloom within a region. Variability in both the timing and magnitude of the bloom in the basin has been evaluated as a function of physical properties in the water column such as Mixed Layer Depth (MLD, GODAS model), sea surface temperature (SST, from AVHRR radiometers), photosynthetically-active radiation (PAR, from ocean color data) and euphotic depth (Z_eu, from ocean color data). The analysis indicated that the timing, size and duration of the phytoplankton bloom in this area are largely controlled by both meteorological and oceanographic conditions at different scales; this means that it is likely to vary widely from one year to another.     

Equatorial anomaly according to the Interkosmos-19 data and IRI model: A comparison

The comparison of the IRI model with the foF2 distribution in the equatorial anomaly region obtained by topside sounding onboard the Interkosmos-19 satellite has been carried out. The global distribution of foF2 in terms of LT-maps was constructed by averaging Intercosmos-19 data for summer, winter, and equinox. These maps, in fact, represent an empirical model of the equatorial anomaly for high solar activity F10.7 ~ 200. The comparison is carried out for the latitudinal foF2 profiles in the characteristic longitudinal sectors of 30, 90, 210, 270, and 330°, as well as for the longitudinal variations in foF2 over the equator. The largest difference between the models (up to 60%) for any season was found in the Pacific longitudinal sector of 210°, where there are a few ground-based sounding stations. Considerable discrepancies, however, are sometimes observed in the longitudinal sectors, where there are many ground-based stations, for example, in the European or Indian sector. The discrepancies reach their maximum at 00 LT, since a decay of the equatorial anomaly begins before midnight in the IRI model and after midnight according to the Interkosmos-19 data. The discrepancies are also large in the morning at 06 LT, since in the IRI model, the foF2 growth begins long before sunrise. In the longitudinal variations in foF2 over the equator at noon, according to the satellite data, four harmonics are distinguished in the June solstice and at the equinox, and three harmonics in the December solstice, while in the IRI model only two and one harmonics respectively are revealed. In diurnal variations in foF2 and, accordingly, in the equatorial anomaly intensity, the IRI model does not adequately reproduce even the main, evening extremum.     

利用EMD方法提取太阳活动周期成分

EMD(经验模态分解)方法在处理非线性及非平稳时间序列时表现出了很大的优势和应用潜力.利用EMD方法研究太阳活动周期,对110年(1894-2003)和55年(1949-2003)的太阳黑子数月均值进行分解,分别得到一系列模式和一个趋势项,其中都可能包含有1.3至1.4年周期分量,25至30个月QBO(准双年振荡)分量,11年太阳周分量和22年Hale周分量.其中11年周期分量幅度最大,变化特征与太阳黑子数原始数据具有很高的相似性.不同于传统方法,EMD方法给出了太阳活动在不同时间尺度上各自分离的变化特征.