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We investigate the dust forecasts from two operational global atmospheric models in comparison with in situ and remote sensing measurements obtained during the AERosol properties – Dust (AER-D) field campaign. Airborne elastic backscatter lidar measurements were performed on board the Facility for Airborne Atmospheric Measurements during August 2015 over the eastern Atlantic, and they permitted us to characterise the dust vertical distribution in detail, offering insights on transport from the Sahara. They were complemented with airborne in situ measurements of dust size distribution and optical properties, as well as datasets from the Cloud–Aerosol Transport System (CATS) spaceborne lidar and the Moderate Resolution Imaging Spectroradiometer (MODIS). We compare the airborne and spaceborne datasets to operational predictions obtained from the Met Office Unified Model (MetUM) and the Copernicus Atmosphere Monitoring Service (CAMS). The dust aerosol optical depth predictions from the models are generally in agreement with the observations but display a low bias. However, the predicted vertical distribution places the dust lower in the atmosphere than highlighted in our observations. This is particularly noticeable for the MetUM, which does not transport coarse dust high enough in the atmosphere or far enough away from the source. We also found that both model forecasts underpredict coarse-mode dust and at times overpredict fine-mode dust, but as they are fine-tuned to represent the observed optical depth, the fine mode is set to compensate for the underestimation of the coarse mode. As aerosol–cloud interactions are dependent on particle numbers rather than on the optical properties, this behaviour is likely to affect their correct representation. This leads us to propose an augmentation of the set of aerosol observations available on a global scale for constraining models, with a better focus on the vertical distribution and on the particle size distribution. Mineral dust is a major component of the climate system; therefore, it is important to work towards improving how models reproduce its properties and transport mechanisms.

This study characterizes a massive African dust intrusion into the Caribbean Basin and southern U.S. in June 2020, which is nicknamed the Godzilla dust plume, using a comprehensive set of satellite and ground-based observations (including MODIS, CALIOP, SEVIRI, AERONET, and EPA Air Quality network) and the NASA GEOS global aerosol transport model. The MODIS data record registered this massive dust intrusion event as the most intense episode over the past two decades. During this event, the aerosol optical depth observed by AERONET and MODIS peaked at 3.5 off the coast of West Africa and 1.8 in the Caribbean Basin. CALIOP observations show that the top of dust plume reached altitudes of 6–8 km in West Africa and descended to about 4 km altitude over the Caribbean Basin and 2 km over the U.S. Gulf coast. The dust plume degraded the air quality in Puerto Rico to the hazardous level, with maximum daily PM10 concentration of 453 μg m−3 recorded on June 23. The dust intrusion into the U.S. raised the PM2.5 concentration on June 27 to a level exceeding the EPA air quality standard in about 40 % of the stations in the southern U.S. Satellite observations reveal that dust emissions from convection-generated haboobs and other sources in West Africa were large albeit not extreme on a daily basis. However, the anomalous strength and northern shift of the North Atlantic Subtropical High (NASH) together with the Azores low formed a closed circulation pattern that allowed for accumulation of the dust near the African coast for about four days. When the NASH was weakened and wandered back to south, the dust outflow region was dominated by a strong African Easterly Jet that rapidly transported the accumulated dust from the coastal region toward the Caribbean Basin, resulting in the record-breaking African dust intrusion. In comparison to satellite observations, the GEOS model well reproduced the MODIS observed tracks of the meandering dust plume as it was carried by the wind systems. However, the model substantially underestimated dust emissions from haboobs and did not lift up enough dust to the middle troposphere for ensuing long-range transport. Consequently, the model largely missed the satellite-observed elevated dust plume along the cross-ocean track and underestimated the dust intrusion into the Caribbean Basin by a factor of more than 4. Modeling improvements need to focus on developing more realistic representations of moist convection, haboobs, and the vertical transport of dust.

Since the first International Cooperative for Aerosol Prediction (ICAP) multi‐model ensemble (MME) study, the number of ICAP global operational aerosol models has increased from five to nine. An update of the current ICAP status is provided, along with an evaluation of the performance of ICAP‐MME over 2012–2017, with a focus on June 2016–May 2017. Evaluated with ground‐based Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) and data assimilation quality MODerate‐resolution Imaging Spectroradiometer (MODIS) retrieval products, the ICAP‐MME AOD consensus remains the overall top‐scoring and most consistent performer among all models in terms of root‐mean‐square error (RMSE), bias and correlation for total, fine‐ and coarse‐mode AODs as well as dust AOD; this is similar to the first ICAP‐MME study. Further, over the years, the performance of ICAP‐MME is relatively stable and reliable compared to more variability in the individual models. The extent to which the AOD forecast error of ICAP‐MME can be predicted is also examined. Leading predictors are found to be the consensus mean and spread. Regression models of absolute forecast errors were built for AOD forecasts of different lengths for potential applications. ICAP‐MME performance in terms of modal AOD RMSEs of the 21 regionally representative sites over 2012–2017 suggests a general tendency for model improvements in fine‐mode AOD, especially over Asia. No significant improvement in coarse‐mode AOD is found overall for this time period., International Cooperative for Aerosol Predictions (ICAP) model 550 nm total AOD RMSE of the 72 h forecast versus corresponding mean AODs for AERONET sites listed in Table 2. Large black dots are ICAP multi‐model ensemble consensus means. Individual models are in small coloured dots. Validation of fine‐ and coarse‐modal AODs and dust AOD is also available in Figure 2.

A record-breaking dust episode took place in Crete on 22 March 2018. The event was characterized by surface concentrations exceeding 1 mg m&minus, 3 for a period of 4&ndash, 7 h, reaching record values higher than 6 mg m&minus, 3 at the background station of Finokalia. We present here a detailed analysis of the atmospheric dynamical processes during this period, to identify the main reasons for such extreme dust advection over Crete. At the synoptic scale, the weakening of the polar vortex and the meridional transport of polar air masses at upper tropospheric layers resulted in a strong jet streak over north Africa and Central Mediterranean and corresponding tropospheric folding that brought cold stratospheric air in mid and upper troposphere. Cyclogenesis occurred at the Gulf of Sirte in Libya, resulting in strong winds over the north-east parts of Libya, enhancing particle emissions. The dust plume traveled at low altitude (0.5&ndash, 3 km) along the warm conveyor belt preceding the depression cold front. This type of dusty southerly wind is commonly known as &ldquo, Khamsin&rdquo, As the flow approached Crete, Foehn winds at the lee side of the island favored the downward mixing of dust towards the surface, resulting in local maxima of PM10 in Heraklion and Finokalia. The analysis is based on the combination of high-resolution WRF-Chem simulations reaching up to 1 &times, 1 km grid space over Crete, ground-based and satellite remote sensing of the dust plumes (PollyXT LiDAR, MSG-SEVIRI, MODIS) and detailed surface aerosol in situ measurements at urban (Heraklion, Chania, Greece) and background (Finokalia) stations in Crete.

In August 2015, the AER-D campaign made use of the FAAM research aircraft based in Cape Verde, and targeted mineral dust. First results will be shown here. The campaign had multiple objectives: (1) lidar dust mapping for the validation of satellite and model products; (2) validation of sunphotometer remote sensing with airborne measurements; (3) coordinated measurements with the CATS lidar on the ISS; (4) radiative closure studies; and (5) the validation of a new model of dustsonde.

Coral reefs rely on inter-habitat connectivity to maintain gene flow, biodiversity and ecosystem resilience. Coral reef communities of the Red Sea exhibit remarkable genetic homogeneity across most of the Arabian Peninsula coastline, with a genetic break towards the southern part of the basin. While previous studies have attributed these patterns to environmental heterogeneity, we hypothesize that they may also emerge as a result of dynamic circulation flow; yet, such linkages remain undemonstrated. Here, we integrate satellite-derived biophysical observations, particle dispersion model simulations, genetic population data and ship-borne in situ profiles to assess reef connectivity in the Red Sea. We simulated long-term (>20 yrs.) connectivity patterns driven by remotely-sensed sea surface height and evaluated results against estimates of genetic distance among populations of anemonefish, Amphiprion bicinctus, along the eastern Red Sea coastline. Predicted connectivity was remarkably consistent with genetic population data, demonstrating that circulation features (eddies, surface currents) formulate physical pathways for gene flow. The southern basin has lower physical connectivity than elsewhere, agreeing with known genetic structure of coral reef organisms. The central Red Sea provides key source regions, meriting conservation priority. Our analysis demonstrates a cost-effective tool to estimate biophysical connectivity remotely, supporting coastal management in data-limited regions.

The Gulf of Aden, situated in the northwest Arabian Sea and linked to the Red Sea, is a relatively unexplored ecosystem. Understanding of large-scale biological dynamics is limited by the lack of adequate datasets. In this study, we analyse 15 years of remotely-sensed chlorophyll-a data (Chl- a , an index of phytoplankton biomass) acquired from the Ocean Colour Climate Change Initiative (OC-CCI) of the European Space Agency (ESA). The improved spatial coverage of OC-CCI data in the Gulf of Aden allows, for the first time, an investigation into the full seasonal succession of phytoplankton biomass. Analysis of indices of phytoplankton phenology (bloom timing) reveals distinct phytoplankton growth periods in different parts of the gulf: a large peak during August (mid-summer) in the western part of the gulf, and a smaller peak during November (mid-autumn) in the lower central gulf and along the southern coastline. The summer bloom develops rapidly at the beginning of July, and its peak is approximately three times higher than that of the autumnal bloom. Remotely-sensed sea-surface temperature (SST), wind-stress curl, vertical nutrient profiles and geostrophic currents inferred from the sea-level anomaly, were analysed to examine the underlying physical mechanisms that control phytoplankton growth. During summer, the prevailing southwesterlies cause upwelling along the northern coastline of the gulf (Yemen), leading to an increase in nutrient availability and enhancing phytoplankton growth along the coastline and in the western part of the gulf. In contrast, in the central region of the gulf, lowest concentrations of Chl- a are observed during summer, due to strong downwelling caused by a mesoscale anticyclonic eddy. During autumn, the prevailing northeasterlies enable upwelling along the southern coastline (Somalia) causing local nutrient enrichment in the euphotic zone, leading to higher levels of phytoplankton biomass along the coastline and in the lower central gulf. The monsoon wind reversal is shown to play a key role in controlling phytoplankton growth in different regions of the Gulf of Aden.

Colocated Spinning Enhanced Visible and Infrared Imager (SEVIRI) retrieved dust optical depths at 0.55 microns, τ055, and Geostationary Earth Radiation Budget (GERB) fluxes at the top of atmosphere are used to provide, for the first time, an observationally based estimate of the cloud-free net direct radiative effect (DRE) of mineral dust aerosol from geostationary satellite observations, providing new insights into the influence of time of day on the magnitude and sign of the shortwave, longwave, and overall net effect during sunlit hours. Focusing on the Geostationary Earth Radiation Budget Intercomparison of Longwave and Shortwave radiation (GERBILS) campaign over North Africa during June 2007, the presence of mineral dust aerosol reduces the outgoing longwave radiation at all times of day with the peak reduction clearly following the diurnal cycle of surface temperature. The instantaneous shortwave DRE shows strong dependencies on pristine sky albedo and solar zenith angle such that the same dust loading can induce a positive or negative value dependent on time of day. However, the area mean net DRE over the GERBILS period is dominated by the longwave component at all sampled times of day, with mineral dust inducing a reduction in outgoing net flux of the order of 10W m−2. Hence, in the mean sense, Saharan dust is found to warm the Earth-atmosphere system over northern Africa and the Middle East.

The Red Sea is a unique marine environment but relatively unexplored. The only available long-term biological dataset at large spatial and temporal scales is remotely-sensed chlorophyll observations (an index of phytoplankton biomass) derived using satellite measurements of ocean colour. Yet such observations have rarely been compared with in situ data in the Red Sea. In this paper, satellite chlorophyll estimates in the Red Sea from the MODIS instrument onboard the Aqua satellite are compared with three recent cruises of in vivo fluorometric chlorophyll measurements taken in October 2008, March 2010 and September to October 2011. The performance of the standard NASA chlorophyll algorithm, and that of a new band-difference algorithm, is found to be comparable with other oligotrophic regions in the global ocean, supporting the use of satellite ocean colour in the Red Sea. However, given the unique environmental conditions of the study area, regional algorithms are likely to fare better and this is demonstrated through a simple adjustment to the band-difference algorithm.

Initial and boundary conditions of dust are still a missing component in atmospheric modeling. In this context, dust models are usually initialized based on their own previous forecasting cycle. As it is obvious, even at the idealized hypothesis of a perfect model run, this approach implies the propagation of numerical diffusion errors. However, recent improvements in remote sensing retrievals of dust optical depth allow the timely generation of dust fields that can be used for assimilation in forecasting atmospheric modeling systems. In this work we present the methodology and preliminary results for the application of MSG/SEVIRI dust retrievals in the atmospheric model NMME-DREAM. First results of the assimilation method are compared with ground photometers (AERONET) and LIDAR (PollyXT) systems during Charadmexp campaign (15 June–15 July 2014). Significant improvement is found mainly over dust sources in Africa and Arabia deserts. The introduction of satellite assimilation methods in dust models provides an additional tool for the improvement of our understanding on the dust-atmosphere interactions and on their possible implications for climate change.

Three ocean colour algorithms, OC4v6, Carder and OC5 were tested for retrieving Chlorophyll-a (Chla) in coastal areas of the Bay of Bengal and open ocean areas of the Arabian Sea. Firstly, the algorithms were run using ~ 80 in situ Remote Sensing Reflectance, (Rrs(λ)) data collected from coastal areas during eight cruises from January 2000 to March 2002 and the output was compared to in situ Chla. Secondly, the algorithms were run with ~ 20 SeaWiFS Rrs(λ) and the results were compared with coincident in situ Chla. In both cases, OC5 exhibited the lowest log10-RMS, bias, had a slope close to 1 and this algorithm appears to be the most accurate for both coastal and open ocean areas. Thirdly the error in the algorithms was regressed against Total Suspended Material (TSM) and Coloured Dissolved Organic Material (CDOM) data to assess the co-variance with these parameters. The OC5 error did not co-vary with TSM and CDOM. OC4v6 tended to over-estimate Chla > 2 mg m−3 and the error in OC4v6 co-varied with TSM. OC4v6 was more accurate than the Carder algorithm, which over-estimated Chla at concentrations > 1 mg m−3 and under-estimated Chla at values 5500 SeaWiFS Rrs(λ) data from coastal to offshore transects in the Northern Bay of Bengal. There was good agreement between OC4v6 and OC5 in open ocean waters and in coastal areas up to 2 mg m−3. There was a strong divergence between Carder and OC5 in open ocean and coastal waters. OC4v6 and Carder tended to over-estimate Chla in coastal areas by a factor of 2 to 3 when TSM > 25 g m−3. We strongly recommend the use of OC5 for coastal and open ocean waters of the Bay of Bengal and Arabian Sea. A Chla time series was generated using OC5 from 2000 to 2003, which showed that concentrations at the mouths of the Ganges reach a maxima (~ 5 mg m−3) in October and November and were 0.08 mg m−3 further offshore increasing to 0.2 mg m−3 during December. Similarly in early spring from February to March, Chla was 0.08 to 0.2 mg m−3 on the east coast of the Bay.

The phytoplankton pigment composition (chlorophylls and carotenoids) from 17 Atlantic Meridional Transect (AMT) cruises over the period 1995–2005 was analysed to determine the distributions of pigments and plankton in the Atlantic Ocean between 50°N and 50°S. Data were quality assured by statistical methods, including regression of total chlorophyll a (TChla) versus accessory pigments (AP) and comparison of the AMT-TChla with contemporary SeaWiFS-TChla (cruises AMT-05 to -17). Comparisons of province-mean TChla (±SD) for in situ and satellite data showed good agreement for each cruise. ‘Taxa-specific’ pigments were used to define phytoplankton functional types (PFTs) for each of the biogeochemical provinces along the AMT. Pigment ratios (e.g. TChla/AP) were analysed for each cruise and for each province as indices (characteristic properties) of particular PFTs. Mostly robust positive correlations were observed between TChla and pigment ratios for different PFTs, for some provinces and most cruises. These were consistent with previous observations. Generally there were no significant trends of mean TChla or pigment ratios within provinces over the period 1995–2005, although the previously reported perturbation due to the 1997–1998 ENSO was evident.

A series of tide-synchronous satellite images, obtained from the Ocean Colour Monitor (OCM) onboard the Indian Remote Sensing Satellite (IRS-P4), in situ measurements and hydrodynamic model simulations were used to describe dispersal pathways and sources of total suspended matter (TSM) in the Gulf of Kachchh, a macrotidal system with insignificant freshwater inputs. Strong alongshore currents are prevalent at the mouth that move in (out) clockwise during flood (ebb) and undergo cyclic, dynamic changes with the tidal phases. The Gulf, unlike other regions of the Indian coastline, has dynamic turbidity that is zonal (very high in the outer Gulf and in the creeks of the Gulf), particularly during flooding, and reduced in the central region throughout the entire tidal cycle. From this dynamic turbidity with regard to the prevalent currents, it is deduced that inland amplifying flood currents draw in TSM-rich offshore waters into the Gulf, and are the major source of turbidity in the outer regions of the Gulf. In the inner Gulf, because of these high-magnitude currents, scouring of the creek bed leads to resuspension to create higher turbidity. Most of the scoured flux sinks off the mouths of these creeks because of the fanning out of ebbing flows from the narrow creeks into the wider Gulf. The areas under specific influence of different sources of turbidity are delineated schematically.

During the 1980s, a rapid increase in the Phytoplankton Colour Index (PCI), a semiquantitative visual estimate of algal biomass, was observed in the North Sea as part of a regionwide regime shift. Two new data sets created from the relationship between the PCI and SeaWiFS chlorophyll a (Chl a) quantify differences in the previous and current regimes for both the anthropogenically affected coastal North Sea and the comparatively unaffected open North Sea. The new regime maintains a 13% higher Chl a concentration in the open North Sea and a 21% higher concentration in coastal North Sea waters. However, the current regime has lower total nitrogen and total phosphorus concentrations than the previous regime, although the molar N: P ratio in coastal waters is now well above the Redfield ratio and continually increasing. Besides becoming warmer, North Sea waters are also becoming clearer (i.e., less turbid), thereby allowing the normally light-limited coastal phytoplankton to more effectively utilize lower concentrations of nutrients. Linear regression analyses indicate that winter Secchi depth and sea surface temperature are the most important predictors of coastal Chl a, while Atlantic inflow is the best predictor of open Chl a; nutrient concentrations are not a significant predictor in either model. Thus, despite decreasing nutrient concentrations, Chl a continues to increase, suggesting that climatic variability and water transparency may be more important than nutrient concentrations to phytoplankton production at the scale of this study.

Tropical ocean ecosystems are predicted to become warmer, more saline, and less fertile in a future Earth. The Red Sea, one of the warmest and most saline environments in the world, may afford insights into the function of the tropical ocean ecosystem in a changing planet. We show that the concentration of chlorophyll and the duration of the phytoplankton growing season in the Red Sea are controlled by the strength of the winter Arabian monsoon (through horizontal advection of fertile waters from the Indian Ocean). Furthermore, and contrary to expectation, in the last decade (1998–2010) the winter Red Sea phytoplankton biomass has increased by 75% during prolonged positive phases of the Multivariate El Nino–Southern Oscillation Index. A new mechanism is reported, revealing the synergy of monsoon and climate in regulating Red Sea greenness.

Monthly chlorophyll-a (Chl-a) concentrations derived from SeaWiFS data for 1997–2005 and chlorophyll measurements from the Atlantic Meridional Transect for 1995–2001 have been analysed to describe seasonal and inter-annual variability of surface Chl-a in the Mauritanian upwelling. There was a moderate to strong correspondence between the seasonal cycles of surface Chl-a and the seasonal cycles of ocean physical and meteorological fields (such as sea-surface temperature, seasurface height, and prevailing wind), with a noticeable exception in 1998 that corresponded to a strong anomalous Chl-a event (� 250% increase) in the Mauritanian upwelling. Alongshore wind-stress and wind-stress curl were found to be the most significant factors controlling the variability of Chl-a (jointly explaining more than 50% of total variance). The biological response to the alongshore wind-stress was immediate, but it lagged the wind-stress curl by 1–2 months (each explaining more than 40% of the total Chl-a variability). These observations also demonstrate a link, hitherto unreported

The analyses of 64 sequential satellite images (October 1999–March 2001) of Indian Remote Sensing Satellite IRS— P4 ocean color monitor (OCM) (bands around 490, 555, and 670 nm) for total suspended matter (TSM), synchronous sea truth data acquisition, and salinity variations have been used to construct dispersal pathways of the surficial fluvial flux into the northern Bay of Bengal during the NE monsoon. From the spatial extent of the plumes of TSM (160–120 km) during October of 1999 and2000, off the mouth of the Himalayan rivers the Ganga andthe Brahmaputra (G–B), it is deduced that fluvial flux does not diminish concurrently with the termination of the southwest (SW) monsoon, as suggestedby time-series trap experiments in the northern bay. During the NE monsoon, the G–B plumes move north to south initially off the mouth, and thereafter advects SW alongshore in the form of coastal sediment plumes, reducing the salinity of the coastal waters along the entire northern bay during October–December. We have observed a strong relation between enhanced episodic discharges of the Ganga–Brahmaputra (G–B) and augmented coastal turbidity during weekly events. It is also observed that even during such short (weekly) events of very high pulse of TSM discharge by the G–B system, the fluvial fluxes do not advect offshore into the deeper regions of the northcentral bay, but are transportedalongshore andd istributedalong the shelf. Our results, therefore, suggest that the reduced recovery of the fluxes in the sediments traps subsequent to the SW monsoon are not linearly related to the magnitude of fluvial flux of the G–B, but stems from the prevalent dispersal patterns. r 2005 Elsevier Ltd. All rights reserved.

Data from seven validation campaigns in the coastal waters of the Bay of Bengal (BOB) were used to develop a regional SPM (suspended particulate matter) algorithm. The in situ data sets for this algorithm are obtained from 86 stations with optical and 68 stations with total SPM measurements encompassing SPM concentrations between 10 and 189 mg l −1 ,w here most of the observations are in shallow (case 2, average depth ∼45 m) waters and a limited number of samples in open case 1 waters. From simple statistical analyses we found a close relationship between SPM concentration and diffuse attenuation coefficient at 555 nm (K 555) in the BOB coastal waters. The linear regression to the fit has ac oeff icient of determination (r 2 ) 0.96 with a standard error of estimates (σ )12. 5m g l −1 for the above SPM range. The algorithm relating K 555 to [L wn443/L wn670] has been evaluated through a regression analysis of radiometric profiles in the BOB. However, the new SPM algorithm overestimates in case 1 waters (SPM range 0.05–25. 0m g l −1 ), wher ea spectra lr eflectance ratio algorithm (Tassan 1994 Appl. Opt. 33 2369–78) appears to produce better results. An integration of both the approaches performs better in generating the routine IRS-P4 OCM (ocean colour monitor) SPM mapped product.

Radiometric observations are carried out to estimate the net shortwave solar radiation in the upper ocean during the Arabian Sea Monsoon Experiment Phase II (ARMEX-II). Radiant heating rates in the Arabian Sea Warm Pool (ASWP) region from in situ radiometric measurements are presented for the first time. The estimated shortwave fluxes (300–700 nm) from the observed data are 101, 62, 40 and 29 W m −2 at 10, 20, 30 and 40 m depths respectively. About 5% of the surface light reaches below 50 m. Heating of the water column by penetrating solar radiation is substantial and estimated to be 0.18, 0.11, 0.08 and 0.07 ◦ Cd ay −1 in the upper 10, 20, 30 and 40 m respectively. Simultaneous observations from space-based sensors (SeaWiFS and IRS-P4 Ocean Colour Monitor) show an increase in solar absorption in regions with enhanced concentration of biologically active constituents.

The Indian remote sensing satellite, IRS-P4 (Oceansat-I) launched on May 26th, 1999 carried two sensors on board, i.e., the Ocean Colour Monitor (OCM) and the Multi-frequency Scanning Microwave Radiometer (MSMR) dedicated for oceanographic research. Sequential data of IRS-P4 OCM has been analysed over parts of both east and west coast of India and a methodology to retrieve sea surface current velocities has been applied. The method is based on matching suspended sediment dispersion patterns, in sequential two time lapsed images. The pattern matching is performed on a pair of atmospherically corrected and geo-referenced sequential images by Maximum Cross-Correlation (MCC) technique. The MCC technique involves computing matrices of cross-correlation coefficients and identifying correlation peaks. The movement of the pattern can be calculated knowing the displacement of windows required to match patterns in successive images. The technique provides actual flow during a specified period by integrating both tidal and wind influences. The current velocities retrieved were compared with synchronous data collected along the east coast during the GSI cruise ST-133 of R.V. Samudra Kaustubh in January 2000. The current data were measured using the ocean current meter supplied by the Environmental Measurement and CONtrol (EMCON), Kochi available with the Geological Survey of India, Marine Wing. This current meter can measure direction and magnitude with an accuracy of ±5‡ and 2% respectively. The measurement accuracies with coefficient of determination (R 2 ) of 0.99, for both magnitude (cm.s-1) and direction (deg.) were achieved.

Changes in phytoplankton dynamics influence marine biogeochemical cycles, climate processes, and food webs, with substantial social and economic consequences. Large-scale estimation of phytoplankton biomass was possible via ocean colour measurements from two remote sensing satellites - the Coastal Zone Colour Scanner (CZCS, 1979-1986) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, 1998-2010). Due to the large gap between the two satellite eras and differences in sensor characteristics, comparison of the absolute values retrieved from the two instruments remains challenging. Using a unique in situ ocean colour dataset that spans more than half a century, the two satellite-derived chlorophyll-a (Chl-a) eras are linked to assess concurrent changes in phytoplankton variability and bloom timing over the Northeast Atlantic Ocean and North Sea. Results from this unique re-analysis reflect a clear increasing pattern of Chl-a, a merging of the two seasonal phytoplankton blooms producing a longer growing season and higher seasonal biomass, since the mid-1980s. The broader climate plays a key role in Chl-a variability as the ocean colour anomalies parallel the oscillations of the Northern Hemisphere Temperature (NHT) since 1948.

The Bay of Bengal is about 2090 km long and 1610 km wide, bordered on the west by Sri Lanka and India, on the north by Bangladesh, and on the east by Myanmar (earlier Burma) and Thailand. The Andaman and Nicobar Islands separate it from the Andaman Sea, its eastern arm. The Bay of Bengal and the Andaman Sea are together defined as the oceanic area north of 5°N, bordered by the Indian subcontinent, Myanmar, Thailand, Malay Peninsula and Sumatra (Fig. 1). This unique semi-enclosed basin experiences seasonally reversing monsoons and depressions, severe cyclonic storms (SCS), and consequently receives a large amount of rainfall and river run-off in the tropics. It also encounters the largest seasonal sea level fluctuations (−40 cm to +54 cm) anywhere on the earth. An interesting characteristic of this area is its low saline surface water caused by large river run off from the Indian subcontinent and Myanmar. The circulation and hydrography of the Bay of Bengal is complex due to the interplay of semi-annually reversing monsoonal winds and the associated heat and freshwater fluxes. Apart from this, the inflow of warm high saline waters of the Arabian Sea, the Persian Gulf and the Red Sea origin and a number of synoptic disturbances (cyclones) originating during both pre-monsoon (May) and post-monsoon (October) period also affects the dispersal pattern in the Bay of Bengal. The impacts of the enormous discharge of riverine fresh water and sediments are least understood.

Before the onset of the south Asian summer monsoon, sea surface temperature (SST) of the north Indian Ocean warms to 30–32°C. Climatological mean mixed layer depth in spring (March–May) is 10–20 m, and net surface heat flux (Q net ) is 80–100 W m−2 into the ocean. Previous work suggests that observed spring SST warming is small mainly because of (1) penetrative flux of solar radiation through the base of the mixed layer (Q pen ) and (2) advective cooling by upper ocean currents. We estimate the role of these two processes in SST evolution from a two-week Arabian Sea Monsoon Experiment process experiment in April–May 2005 in the southeastern Arabian Sea. The upper ocean is stratified by salinity and temperature, and mixed layer depth is shallow (6 to 12 m). Current speed at 2 m depth is high even under light winds. Currents within the mixed layer are quite distinct from those at 25 m. On subseasonal scales, SST warming is followed by rapid cooling, although the ocean gains heat at the surface: Q net is about 105 W m−2 in the warming phase and 25 W m−2 in the cooling phase; penetrative loss Q pen is 80 W m−2 and 70 W m−2. In the warming phase, SST rises mainly because of heat absorbed within the mixed layer, i.e., Q net minus Q pen ; Q pen reduces the rate of SST warming by a factor of 3. In the second phase, SST cools rapidly because (1) Q pen is larger than Q net and (2) advective cooling is ∼85 W m−2. A calculation using time-averaged heat fluxes and mixed layer depth suggests that diurnal variability of fluxes and upper ocean stratification tends to warm SST on subseasonal timescale. Buoy and satellite data suggest that a typical premonsoon intraseasonal cooling event occurs under clear skies when the ocean is gaining heat through the surface. In this respect, premonsoon SST cooling in the north Indian Ocean is different from that due to the Madden-Julian oscillation or monsoon intraseasonal oscillation.

The Atlantic Meridional Transect (AMT) cruises have been operating since 1995 with SeaWiFS satellite ocean colour data being available since September 1997. AMT sampling includes both underway and CTD stations with analysis of chlorophyll-a undertaken through HPLC. Matchups between AMT HPLC and SeaWiFS chlorophyll-a have been analysed using the SeaWiFS 8-day composites, and there is generally a good agreement (R2 from 0.68-0.91, slopes from 0.89-1.08 and intercepts of less than plusmn0.19). However, the long time series has uncovered inconsistencies which could be attributed to biases in the HPLC data once further research is undertaken

A record-breaking dust episode took place in Crete on 22 March 2018. The event was characterized by surface concentrations exceeding 1 mg m−3for a period of 4–7 h, reaching record values higher than 6 mg m−3at the background station of Finokalia. We present here a detailed analysis of the atmospheric dynamical processes during this period, to identify the main reasons for such extreme dust advection over Crete. At the synoptic scale, the weakening of the polar vortex and the meridional transport of polar air masses at upper tropospheric layers resulted in a strong jet streak over north Africa and Central Mediterranean and corresponding tropospheric folding that brought cold stratospheric air in mid and upper troposphere. Cyclogenesis occurred at the Gulf of Sirte in Libya, resulting in strong winds over the north-east parts of Libya, enhancing particle emissions. The dust plume traveled at low altitude (0.5–3 km) along the warm conveyor belt preceding the depression cold front. This type of dusty southerly wind is commonly known as “Khamsin”. As the flow approached Crete, Foehn winds at the lee side of the island favored the downward mixing of dust towards the surface, resulting in local maxima of PM10in Heraklion and Finokalia. The analysis is based on the combination of high-resolution WRF-Chem simulations reaching up to 1 × 1 km grid space over Crete, ground-based and satellite remote sensing of the dust plumes (PollyXT LiDAR, MSG-SEVIRI, MODIS) and detailed surface aerosol in situ measurements at urban (Heraklion, Chania, Greece) and background (Finokalia) stations in Crete

Over the past several years, there has been a rapid development in the number and quality of global aerosol models intended for operational forecasting use. Indeed, most centers with global numerical weather prediction (NWP) capabilities have some program for aerosol prediction. These aerosol models typically have differences in their underlying meteorology as well as aerosol sources, sinks, microphysics and transformations. However, like similar diversity in aerosol climate models, the aerosol forecast models have fairly similar overall bulk error statistics for aerosol optical thickness (AOT)-one of the few aerosol metrics that is globally available. Experience in climate and weather prediction has shown that in situations such as this where there are several independent models, a multi-model ensemble or consensus will be top performing in many key error metrics. Further, multi-model ensembles provide a highly valuable tool for forecasters attempting to predict severe aerosol events. Here we present the first steps in developing a global multi-model aerosol forecasting ensemble intended for eventual operational and basic research use. Drawing from members of the International Cooperative for Aerosol Prediction (ICAP) latest generation of quasi-operational aerosol models, five day AOT forecasts are analyzed for December 2011 through November 2012 from four institutions: ECMWF, JMA, NASA GSFC, and NRL/FNMOC. For dust, we also include the NOAA NGAC product in our analysis. The Barcelona Supercomputing Centre (NMMC) and UK Met office dust product have also recent become available with ICAP, but have insufficient data to be included in this analysis period. A simple consensus ensemble of member and mean AOT fields for modal species (e.g., fine and coarse mode, and a separate dust ensemble) is used to create the ICAP Multi-Model Ensemble (ICAP-MME). The ICAP-MME is run daily at 0Z for 6 hourly forecasts out to 120 h. Basing metrics on comparisons to 21 regionally representative Aerosol Robotic Network (AERONET) sites, all models generally captured the basic aerosol features of the globe. However, there is an overall AOT low bias among models, particularly for high AOT events. Biomass burning regions have the most diversity in seasonal average AOT. The southern oceans, though low in AOT, nevertheless also have high diversity. In regard to root mean square error, as expected the ICAP-MME placed first over all models worldwide, and was typically first or second in ranking against all models at individual sites. These results are encouraging; as more global operational aerosol models come on line, we expect their inclusion in a robust operational multi-model ensemble will provide valuable aerosol forecasting guidance.

Several environmental/physical variables derived from satellite and in situ data sets were used to understand the variability of coccolithophore abundance in the subarctic North Atlantic. The 7-yr (1997–2004) time-series analysis showed that the combined effects of high solar radiation, shallow mixed layer depth ( 89% of the coccolithophore variation. The June 1998 bloom, which was associated with high light intensity, unusually high sea-surface temperature, and a very shallow mixed layer, was found to be one of the most extensive (>995,000 km2) blooms ever recorded. There was a pronounced sea-surface temperature shift in the mid-1990s with a peak in 1998, suggesting that exceptionally large blooms are caused by pronounced environmental conditions and the variability of the physical environment strongly affects the spatial extent of these blooms. Consequently, if the physical environment varies, the effects of these blooms on the atmospheric and oceanic environment will vary as well.