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Mathematical algorithms relate satellite data of ocean color with the surface Chlorophyll-a concentration (Chl-a), a proxy of phytoplankton biomass. These mathematical tools work best when they are adapted to the unique bio-optical properties of a particular oceanic province. Ocean color algorithms should also consider that there are significant differences between datasets derived from different sensors. Common solutions are to provide different parameters for each sensor or use merged satellite data. In this paper, we use satellite data from the Copernicus merged product suite and in situ data from the southernmost part of the California Current System to test two widely used global algorithms, OCx and CI, and a regional algorithm, CalCOFI2. The OCx algorithm yielded the most favorable results. Consequently, we regionalized it and conducted further testing, leading to significant improvements, especially in eutrophic and oligotrophic waters. The database was then separated according to (a) dynamic boundaries in the area, (b) bio-optical properties, and (c) climatic conditions (El Niño/La Niña). Regional algorithms were obtained and tested for each partition. The Chl-a retrievals for each model were tested and compared. The best fit for the data was for the regional algorithms that considered the climatic conditions (El Niño/La Niña). These results will allow for the construction of consistent regionally adapted time series and, therefore, will demonstrate the importance of El Niño/La Niña events on the bio-optical properties of the area. [ABSTRACT FROM AUTHOR]

The surface currents in coastal areas are closely related to the ecological environment and human activities, and are influenced by both local and remote factors of different timescales, resulting in complex genesis and multi-timescale characteristics. In this research, 9-year-long, hourly high-frequency radar (HFR) surface current observations are utilized together with satellite remote sensing reanalysis products and mooring data, and based on the Empirical Orthogonal Function (EOF) and correlation analysis, we revealed the multi-timescale characteristics of the surface currents in Fremantle Sea (32°S), Southwestern Australia, and explored the corresponding driving factors as well as the impact of El Niño-Southern Oscillation (ENSO) on the nearshore currents. Results show that the currents on the slope are dominated by the southward Leeuwin Current (LC), and the currents within the shelf are dominated by winds, which are subject to obvious diurnal and seasonal variations. The strong bathymetry variation there, from a wide shelf in the north to a narrow shelf in this study region, also plays an important role, resulting in the frequent occurrence of nearshore eddies. In addition, the near-zonal winds south of 30°S in winter contribute to the interannual variability of the Leeuwin Current at Fremantle, especially in 2011, when the onshore shelf circulation is particularly strong because of the climatic factors, together with the wind-driven offshore circulation, which results in significant and long-lasting eddies. The southward Leeuwin Current along Southwestern Australia shows a strong response to interannual climatic variability. During La Niña years, the equatorial thermal anomalies generate the westward anomalies in winds and equatorial currents, which in turn strengthen the Leeuwin Current and trigger the cross-shelf current as well as downwelling within the shelf at Fremantle, whereas during El Niño years, the climate anomalies and the response of coastal currents are opposite. This paper provides insights into the multi-timescale nature of coastal surface currents and the relative importance of different driving mechanisms. It also demonstrates the potential of HFR to reveal the response of nearshore currents to climate anomalies when combined with other multivariate data. Meanwhile, the methodology adopted in this research is applicable to other coastal regions with long-term available HFR observations. [ABSTRACT FROM AUTHOR]

This paper shows more evidence for the existing spatial–temporal synchronization of the air surface temperature and pressure within the lower stratospheric ozone, which is unevenly distributed over the globe. The focus of this study is put on the region of formation and manifestation of El Niño Southern Oscillation (ENSO). Statistical analysis of data (covering the period 1900–2019) displays a well pronounced covariance of ozone at 70 hPa with (i) Nino3.4 index, (ii) air surface temperature, and (iii) sea level pressure, in each grid-point with spatial resolution of 5° in latitude and longitude. The ozone impact could be found at different time scales—from interannual (altering the ENSO phase transition) to interdecadal. Moreover, the centers of action of ozone on the sea level temperature and pressure are positioned at different places, depending on the temporal scale of variability—from the tropical Central Pacific—at interannual and interdecadal, to extratropics—at subdecadal time scales. We show also that positive ozone anomalies at 70 hPa trigger a cooling of the sea surface, with a delay of 9 record's time intervals. The ozone depletion, on the other side, is followed by a sea level warming with a delay of 1–2 record's time intervals. [ABSTRACT FROM AUTHOR]

In the summer of 2022, Pakistan experienced a severe flood event that brought great destruction to the local people and ecosystem. However, there is no comprehensive study on the process, spread and causes of this flood. Therefore, we combined multiple satellite gravity data, meteorological data, hydrological data, and satellite remote sensing data to conduct a thorough investigation and study of this flood. The results show that a 20-year time series of the terrestrial water storage change based multiple gravity data has the high accuracy and reliability, which is used for detecting the flood. The flood propagated through meteorological system (three months), agricultural system (six months) and terrestrial ecosystems (five months), respectively, and the two southern provinces (Balochistan and Sindh) are the most affected by the flood, whose flood severity is 6.955 and 9.557, respectively. The center of the severe flood is located at the border region between the above two province. The severe flood is attributed primarily to the global extreme climate events (La Niña and negative Indian Ocean Dipole events) that altered the transport path of water vapor in the Indian Ocean, causing large amounts of water vapor to converge over Pakistan, resulting in heavy precipitation, and secondarily to the melting of extensive glacier in the mountainous of northern Pakistan as a result of the high temperature in March-May 2022. The above results contribute to the understanding of the mechanism of the impact of extreme climate events on the regional climate, and provide some references for the study of severe floods. [ABSTRACT FROM AUTHOR]

A rare compound hot and drought (CHD) event occurred in the Yangtze River Basin (YRB) in the summer of 2022, which brought serious social crisis and ecological disaster. The analysis of the causes, spatiotemporal characteristics and impacts of this event is of great significance and value for future drought warning and mitigation. We used the Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GRACE-FO) data, meteorological data, hydrological data and satellite remote sensing data to discuss the spatiotemporal evolution, formation mechanism and the influence of the CHD event. The results show that the drought severity caused by the CHD event was the most severe during 2003 and 2022. The CHD event lasted a total of five months (from July to November), and there were variations in the damage in different sub-basins. The Wu River Basin (WRB) is the region where the CHD event lasted the longest, at six months (from July to December), while it also lasted four or five months in all the other basins. Among them, the WRB, Dongting Lake Rivers Basin (DLRB) and Mainstream of the YRB (MSY) are the three most affected basins, whose hot and drought severity values are 7.750 and −8.520 (WRB), 7.105 and −9.915 (DLRB) and 6.232 and −9.143 (MSY), respectively. High temperature and low precipitation are the direct causes of the CHD event, and the underlying causes behind this event are the triple La Niña and negative Indian Ocean Dipole event. The two extreme climate events made the Western Pacific Subtropical High (WPSH) unusually strong, and then the WPSH covered a more northerly and westerly region than in previous years and remained entrenched for a long period of time over the YRB and its adjacent regions. Moreover, this CHD event had a devastating impact on local agricultural production and seriously disrupted daily life and production. Our results have implications for the study of extreme disaster events. [ABSTRACT FROM AUTHOR]

In recent years, Geoscience Australia has undertaken a successful continental-scale validation program, targeting Landsat and Sentinel analysis-ready data surface reflectance products. The field validation model used for this program was successfully built upon earlier studies, and the measurement uncertainties associated with these protocols have been quantified and published. As a consequence, the Australian earth observation community was well-prepared to respond to the United States Geological Survey (USGS) call for collaborators with the 2021 Landsat 8 (L8) and Landsat 9 (L9) underfly. Despite a number of challenges, seven validation datasets were captured across five sites. As there was only a single 100% overlap transit across Australia, and the country was amidst a strong La Niña climate cycle, it was decided to deploy teams to the two available overpasses with only 15% side lap. The validation sites encompassed rangelands, chenopod shrublands, and a large inland lake. Apart from instrument problems at one site, good weather enabled the capture of high-quality field data allowing for meaningful comparisons between the radiometric performance of L8 and L9, as well as the USGS and Australian Landsat analysis-ready data processing models. Duplicate (cross-calibration) spectral sampling at different sites provides evidence of the field protocol reliability, while the off-nadir view of L9 over the water site has been used to better compare the performance of different water and atmospheric correction processing models. [ABSTRACT FROM AUTHOR]

El Niño–Southern Oscillation (ENSO) has remarkable impacts on Tibetan Plateau (TP) summer precipitation. However, recently identified ENSO spatial diversity brings complexity to these impacts. This study investigates the distinct impacts of the Eastern Pacific (EP) and Central Pacific (CP) ENSOs on TP summer precipitation based on numerous precipitation data and satellite-observed and reanalyzed circulation data. The results show that the EP El Niño and the CP La Niña have opposite effects on summer precipitation in the southwestern TP, with significant decreases and increases, respectively, indicating a trans-type inversion. In contrast, the CP El Niño causes significant decreases in summer precipitation in the central-eastern TP. No significant anomaly occurs during the EP La Niña. Moisture budget and circulation analyses suggest that these distinct precipitation characteristics can be attributed to different atmospheric teleconnections, which provide varying vertical motion and moisture conditions. The EP El Niño triggers an atmospheric response similar to the Indian Summer Monsoon–East Asian Summer Monsoon teleconnection, and the CP La Niña generates a teleconnection in the opposite phase. In contrast, the CP El Niño mainly causes a teleconnection resembling the East Asian–Pacific pattern. This study may deepen our understanding of ENSO impacts on TP summer precipitation and have implications for regional climate predictions. [ABSTRACT FROM AUTHOR]

A long-term archive of cloud properties (cloud top pressure, CTP; and cloud effective emissivity, ε) determined from High-resolution Infrared Radiation Sounder (HIRS) data is investigated for evidence of regional cloud cover change. In the 17 years between 1985 and 2001, different cloud types are analysed over the Australian region (10° S–45° S, 105° E–160° E) and areas of change in total cloud frequency examined. Total cloud frequency change over the Australian region between two adjacent eight-year time periods (1994 to 2001 minus 1985 to 1992) shows the largest increases (ranges between 6% and 12%) of average HIRS total cloud cover occurring over the offshore regions to the northwest and northeast of the continent. Over land, the largest reduction of average HIRS total cloud frequency is in the southwestern region of Australia (between 2% and 8%). Through central Australia, there is a 2% to 7% increase in average HIRS total cloud frequency when comparing these eight-year periods. This paper examines the regional cloud changes in 17 years over Australia that are embedded in global cloud statistics. Examining total HIRS cloud cover frequency over Australia and comparing two different eight-year time periods, has highlighted notable areas of average change. Preliminary reporting of satellite-derived HIRS cloud products and Global Precipitation Climatology Project (GPCP) rainfall products during La Niña seasons between 1985 and 2001 has also been undertaken. [ABSTRACT FROM AUTHOR]

Model error is an important source of uncertainty that significantly reduces the accuracy of El Niño–Southern Oscillation (ENSO) prediction. In this study, ensemble coupled data assimilation was employed to estimate the tendency error of the fifth-generation Lamont–Doherty Earth observation (LDEO5) model, which represented the comprehensive effect of different sources of errors. Then, the estimated tendency error was applied to an ensemble prediction system for ENSO prediction. Assimilation experiments showed that tendency error estimation yielded better analysis than state estimation only. With tendency error estimation, simulated state variables such as zonal wind stress anomalies and subsurface temperature anomalies in the Niño3.4 region and upper layer depth anomalies along the equator showed good agreement with their reanalyzed counterparts. The ensemble ENSO prediction system with tendency error estimation demonstrated significantly better prediction skill than the ensemble system without tendency error estimation or the original LDEO5 model, especially for long lead times. The tendency error estimation improved the prediction skill for El Niño more than for La Niña. This study provides a promising approach to further improve prediction skill by reducing model error effects in an ensemble prediction. [ABSTRACT FROM AUTHOR]

El Niño-Southern Oscillation (ENSO) is the most significant global ocean–atmosphere coupled signal in the tropical Pacific Ocean, and it can affect the stratosphere. However, the ENSO-related dynamical processes that influence the ozone valley during summer are still not well understood and are under-investigated. In this study, we used the ERA5 and MERRA-2 reanalysis data from 1979 to 2021 combined with numerical simulations to analyze the mechanisms through which ENSO affects the ozone valley over the Tibetan Plateau in the upper troposphere and the lower stratosphere (UTLS) in summer. The results showed that the two cores of the ozone valley in UTLS were more evident in the summer following La Niña than in the summer following El Niño. At low latitudes, negative O3 anomalies in UTLS were observed in the summer following El Niño and positive O3 anomalies were observed in the summer following La Niña. At middle latitudes, negative O3 anomalies in UTLS were found near 60°E in the summer following El Niño, while negative anomalies were found at 40°E and 120°E in the summer following La Niña. The analysis of the flow and vorticity fields suggested that the field anomalies can cause vertical motion, which in turn leads to the mixing of different ozone concentrations and affects the ozone valley in UTLS over the Tibetan Plateau. In particular, the warming of the Indian Ocean sea-surface temperature (SST) in the summer following El Niño enhances the South Asian High (SAH) through two-stage thermal adaptation, leading to ozone anomalies at low latitudes in the ozone-valley region. These conclusions were verified by a simulation using the WACCM4 model, the results of which were consistent with the original observations. [ABSTRACT FROM AUTHOR]

The southern Bay of Bengal (BOB) cold pool (SCP) plays an important role in the regional climate fluctuation of the BOB. However, the interannual variability in the SCP is still unknown. Multisource satellite remote sensing data and assimilation have been applied to explore the interannual variability in the SCP and its relationship with El Niño–Southern Oscillation (ENSO) events for the period 1982–2020. The anomalous SST of the SCP in the summer following the peak phase (i.e., winter) of the ENSO was closely related to the ENSO events. El Niño (La Niña)-induced the warm (cold) anomaly of the SCP starting from May and persisted throughout August with a peak value appearing in June during the El Niño (La Niña) decaying years. In the El Niño decaying years, the southwest monsoon current (SMC) was weakened, forced locally by the weakening southwesterly wind and remotely by the easterly wind anomaly at the equator associated with El Niño. The El Niño-related weakening SMC and the associated less cold advection led to the warm anomaly of the SCP. In addition, El Niño-related atmospheric heating also made a comparable contribution to the evolution of the SCP's SST. In the early stage (15 May to 10 June), its contribution to the warming of the SCP was much larger than that of the SMC, whereas from mid-June to August, it reversed to have a cooling effect and partially offset the advection heating induced by the SMC on the SCP. In the La Niña decaying years, similar oceanic and atmospheric processes operated but in an opposite way. [ABSTRACT FROM AUTHOR]

The long-term stability and sustainability of offshore wind energy resources are very important for wind energy exploration. In this study, the Cyclostationary Empirical Orthogonal Function (CSEOF) method, which can determine the time varying spatial distributions and long-term fluctuations in the cyclostationary geophysical process, was adopted to investigate the geographical and temporal variability of offshore wind resources in China Seas. The CSEOF analysis was performed on wind speeds at 70 m height above the sea surface from a validated combined Quick Scatterometer (QuikSCAT) and Advanced Scatterometer (ASCAT) wind product (2000–2016) with high spatial resolution of 12.5 km, and Climate Forecast System Reanalysis (CFSR) wind data (1979–2016) with a grid size of 0.5° × 0.5°. The decomposition results of the two datasets indicate that the first CSEOF mode represents the variability of wind annual cycle signal and contributes 77.7% and 76.5% to the wind energy variability, respectively. The principal component time series (PCTS) shows an interannual variability of annual wind cycle with a period of 3–4 years. The second mode accounts for 4.3% and 4.7% of total wind speed variability, respectively, and captures the spatiotemporal contribution of El Niño Southern Oscillation (ENSO) on regional wind energy variability. The correlations between the mode-2 PCTS of scatterometer or CFSR winds and the Southern Oscillation Index (SOI) are greater than 0.7, illustrating that ENSO has a significant impact on China's offshore wind resources. Moreover, the mode-1 or mode-2 spatial pattern of CFSR winds is basically consistent with that of scatterometer data, but CFSR underestimates the temporal variability of annual wind speed cycle and the spatial changes of wind speed related to ENSO. Compared with reanalysis data, scatterometer winds always demonstrate a finer structure of wind energy variability due to their higher spatial resolution. For ENSO events with different intensities, the impact of ENSO on regional wind resources varies with time and space. In general, El Niño has reduced wind energy in most regions of China Seas except for the Bohai Sea and Beibu Bay, while La Niña has strengthened the winds in most areas except for the Bohai Sea and southern South China Sea. [ABSTRACT FROM AUTHOR]

The Asian–Australian Monsoon (AAM), the El Nino-Southern Oscillation (ENSO), and the Indian Ocean Dipole (IOD) have been known to induce variability in ocean surface characteristics along the southern coast of Lesser Sunda Island (LSI). However, previous studies used low spatial resolution data and little Ekman dynamics analysis. This study aims to investigate the direct influence of AAM winds on ocean surface conditions and to determine how ENSO and IOD affect the ocean surface and depth with higher spatial resolution data. In addition, the variability in Ekman dynamics is also described along with the inconsistent relationship between wind and sea surface temperature (SST) in four different areas. The results indicate that persistent southeasterly winds are likely to induce low SST and chlorophyll-a blooms. Based on the interannual variability, the positive chlorophyll-a (up to 0.5 mg m−3) and negative SST (reaching −1.5 °C) anomalies observed in the El Nino of 2015 coincide with +IOD, which also corroborates positive wind stress and Ekman Mass Transport (EMT) anomalies. In contrast, the La Nina of 2010 coincides with -IOD, and positive SST and negative chlorophyll-a anomalies (more than 1.5 °C and −0.5 mg m−3 respectively) were observed. Furthermore, we found that southern coast of Java and Bali Island have a different generated mechanism that controls SST variability. [ABSTRACT FROM AUTHOR]

This paper shows more evidence for the existing spatial–temporal synchronization of the air surface temperature and pressure within the lower stratospheric ozone, which is unevenly distributed over the globe. The focus of this study is put on the region of formation and manifestation of El Niño Southern Oscillation (ENSO). Statistical analysis of data (covering the period 1900–2019) displays a well pronounced covariance of ozone at 70 hPa with (i) Nino3.4 index, (ii) air surface temperature, and (iii) sea level pressure, in each grid-point with spatial resolution of 5° in latitude and longitude. The ozone impact could be found at different time scales—from interannual (altering the ENSO phase transition) to interdecadal. Moreover, the centers of action of ozone on the sea level temperature and pressure are positioned at different places, depending on the temporal scale of variability—from the tropical Central Pacific—at interannual and interdecadal, to extratropics—at subdecadal time scales. We show also that positive ozone anomalies at 70 hPa trigger a cooling of the sea surface, with a delay of 9 record’s time intervals. The ozone depletion, on the other side, is followed by a sea level warming with a delay of 1–2 record’s time intervals.

Indo-Pacific sea surface temperature dynamics play a prominent role in Asian summer monsoon variability. Two interactive climate modes of the Indo-Pacific-the El Niño/Southern Oscillation (ENSO) and the Indian Ocean dipole mode-modulate the amount of precipitation over India, in addition to precipitation over Africa, Indonesia, and Australia. However, this modulation is not spatially uniform. The precipitation in southern India is strongly forced by the Indian Ocean dipole mode and ENSO. In contrast, across northern India, encompassing the Ganges and Brahmaputra basins, the climate mode influence on precipitation is much less. Understanding the forcing of precipitation in these river basins is vital for food security and ecosystem services for over half a billion people. Using 28 years of remote sensing observations, we demonstrate that (i) the tropical west-east differential heating in the Indian Ocean influences the Ganges precipitation and (ii) the north-south differential heating in the Indian Ocean influences the Brahmaputra precipitation. The El Niño phase induces warming in the warm pool of the Indian Ocean and exerts more influence on Ganges precipitation than Brahmaputra precipitation. The analyses indicate that both the magnitude and position of the sea surface temperature anomalies in the Indian Ocean are important drivers for precipitation dynamics that can be effectively summarized using two new indices, one tuned for each basin. These new indices have the potential to aid forecasting of drought and flooding, to contextualize land cover and land use change, and to assess the regional impacts of climate change. [ABSTRACT FROM AUTHOR]

El Niño-Southern Oscillation (ENSO) is regarded as the main driver of phytoplankton inter-annual variability. Remotely sensed surface chlorophyll-a (Chl-a), has made it possible to examine phytoplankton variability at a resolution and scale that allows for the investigation of climate signals such as ENSO. We provide empirical evidence of an immediate and lagged influence of ENSO on SeaWiFS and MODIS-Aqua derived global Chl-a concentrations. We use 13 years of Chl-a remotely sensed observations along with sea surface temperature (SST) observations across the Tropical and South Pacific to isolate and examine the spatial development of Chl-a anomalies during ENSO: its canonical or eastern Pacific (EP) mode, and El Niño Modoki or central Pacific (CP) mode, using the extended empirical orthogonal function (EEOF) technique. We describe how an EP ENSO phase transition affects Chl-a, and identify an interannual CP mode of variability induced spatial pattern. We argue that when ENSO is analysed as a propagating signal by the EEOF, CP ENSO is found to be more influential on Chl-a interannual to decadal variability than the canonical EP ENSO. Our results cannot confirm the independence of the two ENSO modes but clearly demonstrate that both ENSO flavors manifest a distinct OPEN ACCESS biological response. [ABSTRACT FROM AUTHOR]

Lakes are sensitive indicators of climate change in the Tibetan Plateau (TP), which have shown high temporal and spatial variability in recent decades. The driving forces for the change are still not entirely clear. This study examined the area change of the lakes greater than 1 km2 in the endorheic basins of the Tibetan Plateau (EBTP) using Landsat images from 1990 to 2019, and analysed the relationships between lake area and local and large-scale climate variables at different geographic scales. The results show that lake area in the EBTP has increased significantly from 1990 to 2019 at a rate of 432.52 km2·year−1. In the past 30 years, lake area changes in the EBTP have mainly been affected by local climate variables such as precipitation and temperature. At a large scale, Indian Summer Monsoon (ISM) has correlations with lake area in western sub-regions in the Inner Basin (IB). While Atlantic Multidecadal Oscillation (AMO) has a significant connection with lake area, the North Atlantic Oscillation (NAO) does not. We also found that abnormal drought (rainfall) brought by the El Niño/La Niña events are significantly correlated with the lake area change in most sub-regions in the IB. [ABSTRACT FROM AUTHOR]

Falling between seasonal cycle variability and the impact of local drivers, the sea level in the Red Sea and Gulf of Aden has been given less consideration, especially with large-scale modes. With multiple decades of satellite altimetry observations combined with good spatial resolution, the time has come for diagnosis of the impact of large-scale modes on the sea level in those important semi-enclosed basins. While the annual cycle of sea level appeared as a dominant cycle using spectral analysis, the semi-annual one was also found, although much weaker. The first empirical orthogonal function mode explained, on average, about 65% of the total variance throughout the seasons, while their principal components clearly captured the strong La Niña event (1999–2001) in all seasons. The sea level showed a strong positive relation with positive phase El Niño Southern Oscillation in all seasons and a strong negative relation with East Atlantic/West Russia during winter and spring over the study period (1993–2017). We show that the unusually stronger easterly winds that are displaced north of the equator generate an upwelling area near the Sumatra coast and they drive both warm surface and deep-water masses toward the West Indian Ocean and Arabian Sea, rising sea level over the Red Sea and Gulf of Aden. This process could explain the increase of sea level in the basin during the positive phase of El Niño Southern Oscillation events. [ABSTRACT FROM AUTHOR]

The Marquesas form an isolated group of small islands in the Central South Pacific where quasi-permanent biological activity is observed. During La Niña events, this biological activity, shown by a net increase of chlorophyll-a concentration (Chl, a proxy of phytoplankton biomass), is particularly strong. It has been hypothesized that this strong activity is due to iron-rich waters advected from the equatorial region to the Marquesas by tropical instability waves (TIWs). Here we investigate this hypothesis over 18 years by combining satellite observations, re-analyses of ocean data, and Lagrangian diagnostics. Four La Niña events ranging from moderate to strong intensity occurred during this period, and our results show that the Chl plume within the archipelago can be indeed influenced by such equatorial advection, but this was observed during the strong 1998 and 2010 La Niña conditions only. Chl spatio-temporal patterns during the occurrence of other TIWs rather suggest the interaction of large-scale forcing events such as an uplift of the thermocline or the enhancement of coastal upwelling induced by the tropical strengthening of the trades with the islands leading to enhancement of phytoplankton biomass within the surface waters. Overall, whatever the conditions, our analyses suggest that the influence of the TIWs is to disperse, stir, and, therefore, modulate the shape of the existing phytoplankton plume. [ABSTRACT FROM AUTHOR]