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.     

Rainfall estimation over a Mediterranean region using a method based on various spectral parameters of SEVIRI-MSG

The ultimate objective of this paper is the estimation of rainfall over an area in Algeria using data from the SEVIRI radiometer (Spinning Enhanced Visible and Infrared Imager). To achieve this aim, we use a new Convective/Stratiform Rain Area Delineation Technique (CS-RADT). The satellite rainfall retrieval technique is based on various spectral parameters of SEVIRI that express microphysical and optical cloud properties. It uses a multispectral thresholding technique to distinguish between stratiform and convective clouds. This technique (CS-RADT) is applied to the complex situation of the Mediterranean climate of this region. The tests have been conducted during the rainy seasons of 2006/2007 and 2010/2011 where stratiform and convective precipitation is recorded. The developed scheme (CS-RADT) is calibrated by instantaneous meteorological radar data to determine thresholds, and then rain rates are assigned to each cloud type by using radar and rain gauge data. These calibration data are collocated with SEVIRI data in time and space.     

Coastal sea level measurements using a single geodetic GPS receiver

This paper presents a method to derive local sea level variations using data from a single geodetic-quality Global Navigation Satellite System (GNSS) receiver using GPS (Global Positioning System) signals. This method is based on multipath theory for specular reflections and the use of Signal-to-Noise Ratio (SNR) data. The technique could be valuable for altimeter calibration and validation. Data from two test sites, a dedicated GPS tide gauge at the Onsala Space Observatory (OSO) in Sweden and the Friday Harbor GPS site of the EarthScope Plate Boundary Observatory (PBO) in USA, are analyzed. The sea level results are compared to independently observed sea level data from nearby and in situ tide gauges. For OSO, the Root-Mean-Square (RMS) agreement is better than 5 cm, while it is in the order of 10 cm for Friday Harbor. The correlation coefficients are better than 0.97 for both sites. For OSO, the SNR-based results are also compared with results from a geodetic analysis of GPS data of a two receivers/antennae tide gauge installation. The SNR-based analysis results in a slightly worse RMS agreement with respect to the independent tide gauge data than the geodetic analysis (4.8 cm and 4.0 cm, respectively). However, it provides results even for rough sea surface conditions when the two receivers/antennae installation no longer records the necessary data for a geodetic analysis.     

太阳活动、黑潮海温年季变化与长江中游旱涝灾害

本文采用太阳１０．７ｃｍ辐射流量（Ｆ１０．７）作为太阳活动指标，根据最近３０多年的太阳活动、西太平洋黑潮区海温和长江中游干支流地区雨量观测数据，分析了三者之间的关系，研究发现长江中游地区旱涝明显地受太阳活动和黑潮海温年季变化的共同控制．可根据某些特征，利用两年之前的太阳１０．７ｃｍ辐射流量和当年春季之前黑潮海温的观测数据，分析判断长江中游当年夏季是否发生旱涝灾害的趋势．     

A study on Nighttime Winter Anomaly (NWA) and other related Mid-latitude Summer Nighttime Anomaly (MSNA) in the light of International Reference Ionosphere (IRI) – Model

The ionospheric Nighttime Winter Anomaly (NWA) is a feature observed in the Northern Hemisphere at the American and in the Southern Hemisphere at the Asian longitude sector under low solar activity conditions. Jakowski et al. (2015) analyzed ground-based GPS derived TEC and peak electron density data from radio occultation measurements on Formosat-3/COSMIC satellites and confirmed the persistence of the phenomenon. Further, they assumed that Mid-latitude Summer Nighttime Anomaly (MSNA) and related special anomalies such as the Weddell Sea Anomaly (WSA) and the Okhotsk Sea Anomaly (OSA) are closely related to the NWA via enhanced wind-induced uplifting of the ionosphere. The aim of this paper is to study the factors causing these anomalies and also to investigate if these anomalies are re-produced by IRI. The results show that IRI model does include the NWA effect, though at a different longitude and could be improved for better predictions. The IRI-2016 model does show WSA in TEC but not in NmF2. Further, the IRI-2016 model could clearly predict the OSA both in NmF2 and TEC.     

Exploiting the Sentinel-3 tandem phase dataset and azimuth oversampling to better characterize the sensitivity of SAR altimeter sea surface height to long ocean waves

Being the very first SAR mode altimeter tandem phase, the Sentinel-3 A/B tandem phase has provided an unprecedented opportunity to better characterize the sensitivity of SAR altimetry retrievals to high-frequency processes, such as long ocean waves. In this paper, we show that for some sea-state conditions, that are still to be precisely characterized, long ocean waves are responsible for high-frequency (spatial and temporal) coherent Sea Level Anomaly (SLA) signals. It is found that the peak wavelength corresponds to the dominant swell wavelength. Furthermore, the short time lag between S3-A and S3-B acquisitions allows performing cross-spectral analyses that reveal phase shifts consistent with waves travelling according to the wave dispersion relation. It is also demonstrated that the classical 20 Hz sampling frequency is insufficient to properly sample most swell-induced SLA signals and that aliasing can generate errors over the entire frequency spectrum, including at long wavelengths. These results advocate for the use of azimuth oversampling (40 Hz or 80 Hz). Low-pass filtering should be applied prior to any down-sampling to 20 Hz, in order to prevent long-wavelength errors induced by spectral leakage.     

Satellite ocean colour algorithm for Prochlorococcus, Synechococcus, and picoeukaryotes concentration retrieval in the South China Sea

An algorithm for retrieval of surface waters cell concentrations (in cell/ml) for three picophytoplankton components, Prochlorococcus (Pro), Synechococcus (Syn), and picoeukaryotes (Peuk) in the South China Sea (SCS), from ocean colour satellite data was developed and tested. Level 3 merged multisensor Ocean Colour Climate Change Initiative satellite data is used. Training is performed using in situ data on abundances of the three phytoplankton components. Several predictors derived from satellite reflectance data were tested. The regression form that assures the highest accuracy of the algorithm was chosen based on cross-validation (CV). According to the CV on test data subset, the algorithm performance is characterized by the r value 0.89, 0.72, and 0.73 and MAPD 38, 71 and 51% for Peuk, Pro, and Syn respectively. This is one of the few studies aimed at the Peuk, Pro, and Syn distribution research in the northern SCS using ocean colour satellite data. This is the only research providing algorithm with accuracy estimates of the Peuk, Pro, and Syn concentrations retrieval from the ocean colour data. Analysis of the developed algorithm allows us to conclude that both mechanisms (specific spectral features caused by pigments composition and spectrum features sensitive to general primary productivity, e.g. band ratios in 443–510?nm range and spectrum absolute values) are important for getting accurate information on the picophytoplankton composition.     

Multi- GNSS reflectometry performance evaluation for coastal sea level monitoring: A case study in Antarctic Peninsula

Antarctica is a continent that crucial for studying climate change and its progression across time, as well as analyzing and forecasting local and global change. In this environment, due to the challenges caused by sea-level rise, storm surges, and tsunamis, sustainability is a critical concern, particularly for coastal regions. As a result, the long-term observations that will be conducted in Antarctica are critical for monitoring the adverse impacts of climate change. In recent years, many monitoring approaches, both space, and ground-based are performed to monitor sea/ice level trends in space-based scientific investigations conducted in and around the region. In the study, based on one year of observations from the Palmer GNSS Station, the GNSS Reflectometry technique was used to measure the sea level on the Antarctic Peninsula (PALM). GNSS Station observations were analyzed with a Lomb-Scargle periodogram to monitor sea-level changes, and results were validated with data from a co-located tide gauge (TG). The results show that the correlation between GNSS-R sea-level changes and tidal sea-level changes is found as 0.91.     

Chlorophyll,calcite, and suspended sediment concentrations in the Bay of Bengal and the Arabian Sea at the river mouths

Chlorophyll and suspended sediment concentrations (SSC) and sea surface temperature (SST) are important parameters in assessing the productivity of coastal regions. Numerous rivers flow into the eastern (Ganga, Subernarekha, Mahanadi, Godavari, Krishna, Penner, and Kaveri) and western (Narmada, Tapti, and Indus) coasts of the Indian sub-continent. Using IRS P4 (Oceansat-1) Ocean Color Monitor (OCM) and Moderate Resolution Imaging Spectroradiometer (MODIS) data, we have retrieved chlorophyll, calcite, and SSC near the mouth of these rivers for the period during 2000–2004. The maxima of chlorophyll-a concentrations at the river mouth is much higher for the Himalayan and north India rivers (Ganga, Subernarekha, Mahanadi, and Indus) (10–14 mg/m³) compared to rivers in the southern parts of India (Kaveri and Penner) (∼4 mg/m³). The maxima of calcite concentration (∼45 moles/m³), chlorophyll (∼14 mg/m³), and sediment concentrations (∼9 g/m³) near river mouth are found to be influenced by river discharges (Ganga and Brahmaputra) during the monsoon season. The calcite concentration (∼45 moles/m³) at the mouth of Ganga river shows a major peak with the onset of monsoon season (June–July) followed by a maxima in chlorophyll-a with a time lag of 1–2 months. The Krishna, Kaveri, and Penner rivers show low chlorophyll concentrations (3–8 mg/m³), high calcite (0–40 moles/m³), and low SSC (<3 g/m³) compared to Narmada and Tapti rivers (chlorophyll-a 12–14 mg/m³, calcite 0–2 moles/m³, and SSC 13–19 g/m³). The Indus river shows similar behavior (maxima of chlorophyll ∼13 mg/m³ and SSC ∼8 g/m³) with respect to Ganga river except for high calcite concentration during winter months (∼25 moles/m³). The characteristics of the chlorophyll, calcite, and SSC at the mouth of these rivers show spatial and temporal variability along the eastern and westerns coasts of India which are found to differ widely. A comparison of the chlorophyll concentrations using OCM and MODIS data shows low chlorophyll concentrations in the Bay of Bengal as compared to the Arabian Sea.     

Merged series of normalized water leaving radiances obtained from multiple satellite missions for the Mediterranean Sea

Merging time series of ocean color-derived products provided by independent satellite missions supports related biogeochemical and environmental applications by combining temporally overlapping data sets and by increasing data coverage. The creation of a merged series of normalized water leaving radiances _LWN$L_{\text{WN}}$, the primary ocean color product, is presented for the Mediterranean Sea using the SeaWiFS and MODIS data records. The merging relies on an optically-based technique that combines the available _LWN$L_{\text{WN}}$ signal in a spectrally consistent way. Validation statistics indicate uncertainties associated with the merged _LWN$L_{\text{WN}}$ decreasing from 23% at 412 nm to 12% in the 500- to 555-nm spectral range. The inter-comparison of the sensor-specific products, conducted at the scale of the basin for daily-to-monthly time scales, indicates an overall consistency. The level of differences varies with the wavelength considered and shows a marked seasonal cycle, with differences that tend to be higher in winter. The merged series is remarkably consistent with the sensor-specific data, with average absolute percent differences lower than 10% for all wavelengths below 555 nm. The benefit of merging in terms of sampling frequency over the basin is also illustrated. A merged series of _LWN$L_{\text{WN}}$ data based on the two considered missions provides valid data over 36% of the basin area on a daily basis.