Trade wind cumuli statistics in clean and polluted air over the Indian Ocean from in situ and remote sensing measurements

2004 ◽  
Vol 31 (21) ◽  
pp. n/a-n/a ◽  
Author(s):  
Greg M. McFarquhar ◽  
Steven Platnick ◽  
Larry Di Girolamo ◽  
Hailong Wang ◽  
Gala Wind ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Indian Ocean ◽  
Trade Wind ◽  
The Indian Ocean

scholarly journals Impact of Monsoon-Transported Anthropogenic Aerosols and Sun-Glint on the Satellite-Derived Spectral Remote Sensing Reflectance in the Indian Ocean

2021 ◽  
Vol 13 (2) ◽  
pp. 184
Author(s):  
Rongjie Liu ◽  
Jie Zhang ◽  
Tingwei Cui ◽  
Haocheng Yu
Keyword(s):  
Remote Sensing ◽  
Indian Ocean ◽  
Infrared Imaging ◽  
Atmospheric Correction ◽  
Spatiotemporal Pattern ◽  
Anthropogenic Aerosols ◽  
Remote Sensing Reflectance ◽  
The Indian Ocean ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Terra Modis

Spectral remote sensing reflectance (Rrs(λ), sr−1) is one of the most important products of ocean color satellite missions, where accuracy is essential for retrieval of in-water, bio-optical, and biogeochemical properties. For the Indian Ocean (IO), where Rrs(λ) accuracy has not been well documented, the quality of Rrs(λ) products from Moderate Resolution Imaging Spectroradiometer onboard both Terra (MODIS-Terra) and Aqua (MODIS-Aqua), and Visible Infrared Imaging Radiometer Suite onboard the Suomi National Polar-Orbiting Partnership spacecraft (VIIRS-NPP), is evaluated and inter-compared based on a quality assurance (QA) system, which can objectively grade each individual Rrs(λ) spectrum, with 1 for a perfect spectrum and 0 for an unusable spectrum. Taking the whole year of 2016 as an example, spatiotemporal pattern of Rrs(λ) quality in the Indian Ocean is characterized for the first time, and the underlying factors are elucidated. Specifically, QA analysis of the monthly Rrs(λ) over the IO indicates good quality with the average scores of 0.93 ± 0.02, 0.92 ± 0.02 and 0.92 ± 0.02 for VIIRS-NPP, MODIS-Aqua, and MODIS-Terra, respectively. Low-quality (~0.7) data are mainly found in the Bengal Bay (BB) from January to March, which can be attributed to the imperfect atmospheric correction due to anthropogenic absorptive aerosols transported by the northeasterly winter monsoon. Moreover, low-quality (~0.74) data are also found in the clear oligotrophic gyre zone (OZ) of the south IO in the second half of the year, possibly due to residual sun-glint contributions. These findings highlight the effects of monsoon-transported anthropogenic aerosols, and imperfect sun-glint removal on the Rrs(λ) quality. Further studies are advocated to improve the sun-glint correction in the oligotrophic gyre zone and aerosol correction in the complex ocean–atmosphere environment.

scholarly journals Satellite-observed relationships between aerosol and trade-wind cumulus cloud properties over the Indian Ocean

2011 ◽  
Vol 38 (1) ◽  
pp. n/a-n/a ◽  
Author(s):  
Sagnik Dey ◽  
Larry Di Girolamo ◽  
Guangyu Zhao ◽  
Alexandra L. Jones ◽  
Greg M. McFarquhar
Keyword(s):  
Indian Ocean ◽  
Trade Wind ◽  
Cumulus Cloud ◽  
Cloud Properties ◽  
The Indian Ocean

scholarly journals Thermodynamic structure of the Atmospheric Boundary Layer over the Arabian Sea and the Indian Ocean during pre-INDOEX and INDOEX-FFP campaigns

2004 ◽  
Vol 22 (8) ◽  
pp. 2679-2691 ◽  
Author(s):  
M. V. Ramana ◽  
P. Krishnan ◽  
S. Muraleedharan Nair ◽  
P. K. Kunhikrishnan
Keyword(s):  
Boundary Layer ◽  
Indian Ocean ◽  
Atmospheric Boundary Layer ◽  
Mixed Layer ◽  
Arabian Sea ◽  
Trade Wind ◽  
Back Trajectory ◽  
Spatial And Temporal Variability ◽  
Air Mass ◽  
The Indian Ocean

Abstract. Spatial and temporal variability of the Marine Atmospheric Boundary Layer (MABL) height for the Indian Ocean Experiment (INDOEX) study period are examined using the data collected through Cross-chained LORAN (Long-Range Aid to Navigation) Atmospheric Sounding System (CLASS) launchings during the Northern Hemispheric winter monsoon period. This paper reports the results of the analyses of the data collected during the pre-INDOEX (1997) and the INDOEX-First Field Phase (FFP; 1998) in the latitude range 14°N to 20°S over the Arabian Sea and the Indian Ocean. Mixed layer heights are derived from thermodynamic profiles and they indicated the variability of heights ranging from 400m to 1100m during daytime depending upon the location. Mixed layer heights over the Indian Ocean are slightly higher during the INDOEX-FFP than the pre-INDOEX due to anomalous conditions prevailing during the INDOEX-FFP. The trade wind inversion height varied from 2.3km to 4.5km during the pre-INDOEX and from 0.4km to 2.5km during the INDOEX-FFP. Elevated plumes of polluted air (lofted aerosol plumes) above the marine boundary layer are observed from thermodynamic profiles of the lower troposphere during the INDOEX-FFP. These elevated plumes are examined using 5-day back trajectory analysis and show that one group of air mass travelled a long way from Saudi Arabia and Iran/Iraq through India before reaching the location of measurement, while the other air mass originates from India and the Bay of Bengal.

scholarly journals Improvement of airborne retrievals of cloud droplet number concentration of trade wind cumulus using a synergetic approach

2019 ◽  
Vol 12 (3) ◽  
pp. 1635-1658 ◽  
Author(s):  
Kevin Wolf ◽  
André Ehrlich ◽  
Marek Jacob ◽  
Susanne Crewell ◽  
Martin Wirth ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Cloud Base ◽  
Trade Wind ◽  
Liquid Water Path ◽  
Cloud Properties ◽  
Research Aircraft ◽  
Cloud Droplet Number Concentration

Abstract. In situ measurements of cloud droplet number concentration N are limited by the sampled cloud volume. Satellite retrievals of N suffer from inherent uncertainties, spatial averaging, and retrieval problems arising from the commonly assumed strictly adiabatic vertical profiles of cloud properties. To improve retrievals of N it is suggested in this paper to use a synergetic combination of passive and active airborne remote sensing measurement, to reduce the uncertainty of N retrievals, and to bridge the gap between in situ cloud sampling and global averaging. For this purpose, spectral solar radiation measurements above shallow trade wind cumulus were combined with passive microwave and active radar and lidar observations carried out during the second Next Generation Remote Sensing for Validation Studies (NARVAL-II) campaign with the High Altitude and Long Range Research Aircraft (HALO) in August 2016. The common technique to retrieve N is refined by including combined measurements and retrievals of cloud optical thickness τ, liquid water path (LWP), cloud droplet effective radius reff, and cloud base and top altitude. Three approaches are tested and applied to synthetic measurements and two cloud scenarios observed during NARVAL-II. Using the new combined retrieval technique, errors in N due to the adiabatic assumption have been reduced significantly.

Mechanisms for the Interannual Variability in the Tropical Indian Ocean. Part II: Regional Processes

2007 ◽  
Vol 20 (13) ◽  
pp. 2937-2960 ◽  
Author(s):  
Bohua Huang ◽  
J. Shukla
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
El Niño ◽  
El Nino ◽  
Tropical Indian Ocean ◽  
Global Ocean ◽  
Trade Wind ◽  
Tropical Ocean ◽  
The Indian Ocean ◽  
Sst Anomalies

Abstract To understand the mechanisms of the interannual variability in the tropical Indian Ocean, two long-term simulations are conducted using a coupled ocean–atmosphere GCM—one with active air–sea coupling over the global ocean and the other with regional coupling restricted within the Indian Ocean to the north of 30°S while the climatological monthly sea surface temperatures (SSTs) are prescribed in the uncoupled oceans to drive the atmospheric circulation. The major spatial patterns of the observed upper-ocean heat content and SST anomalies can be reproduced realistically by both simulations, suggesting that they are determined by intrinsic coupled processes within the Indian Ocean. In both simulations, the interannual variability in the Indian Ocean is dominated by a tropical mode and a subtropical mode. The tropical mode is characterized by a coupled feedback among thermocline depth, zonal SST gradient, and wind anomalies over the equatorial and southern tropical Indian Ocean, which is strongest in boreal fall and winter. The tropical mode simulated by the global coupled model reproduces the main observational features, including a seasonal connection to the model El Niño–Southern Oscillation (ENSO). The ENSO influence, however, is weaker than that in a set of ensemble simulations described in Part I of this study, where the observed SST anomalies for 1950–98 are prescribed outside the Indian Ocean. Combining with the results from Part I of this study, it is concluded that ENSO can modulate the temporal variability of the tropical mode through atmospheric teleconnection. Its influence depends on the ENSO strength and duration. The stronger and more persistent El Niño events in the observations extend the life span of the anomalous events in the tropical Indian Ocean significantly. In the regional coupled simulation, the tropical mode is still active, but its dominant period is shifted away from that of ENSO. In the absence of ENSO forcing, the tropical mode is mainly stimulated by an anomalous atmospheric direct thermal cell forced by the fluctuations of the northwestern Pacific monsoon. The subtropical mode is characterized by an east–west dipole pattern of the SST anomalies in the southern subtropical Indian Ocean, which is strongest in austral fall. The SST anomalies are initially forced by surface heat flux anomalies caused by the anomalous southeast trade wind in the subtropical ocean during austral summer. The trade wind anomalies are in turn associated with extratropical variations from the southern annular mode. A thermodynamic air–sea feedback strengthens these subtropical anomalies quickly in austral fall and extends their remnants into the tropical ocean in austral winter. In the simulations, this subtropical variability is independent of ENSO.

Industry-collected target strength of high seas orange roughy in the Indian Ocean

2020 ◽  
Author(s):  
Ben Scoulding ◽  
Rudy Kloser
Keyword(s):  
Indian Ocean ◽  
Cost Effective ◽  
Measurement Range ◽  
Target Strength ◽  
Orange Roughy ◽  
Cost Effective Method ◽  
The Indian Ocean ◽  
State Of The Science ◽  
High Seas

Abstract Visually verified in situ target strengths (TS) are the state of the science for determining the conversion from acoustic echo-integration surveys to biomass. Here, we show how these measurements can be made by high seas fisheries during normal operations using a net-attached acoustic optical system (AOS) without specialized personnel on board. In situ TS were collected from ∼45 cm standard length (SL) orange roughy (Hoplostethus atlanticus) in the southern Indian Ocean at 38 and 120 kHz. We use a multiple lines of evidence approach to demonstrate that the previous TS–SL equation developed for ∼10 cm smaller fish in Australia and New Zealand is not suitable for the larger orange roughy and instead propose new TS–SL equations. Our findings show that biomass estimates at 38 kHz will be reduced by ∼58% when using this new TS–SL compared to the existing TS–SL for smaller fish. This highlights the error of extrapolating TS–SL equations outside the measurement range. For this high sea region, the net-attached AOS represented a practical cost-effective method to obtain measurements and provide a result that could be used to inform the management of the stocks. We suggest that this method would be useful in all deep-water fisheries to monitor the TS of the fish for a range of environmental and ontogenetic conditions.

scholarly journals Atmospheric CO and CH<sub>4</sub> time series and seasonal variations on Reunion Island from ground-based in situ and FTIR (NDACC and TCCON) measurements

2018 ◽  
Vol 18 (19) ◽  
pp. 13881-13901 ◽  
Author(s):  
Minqiang Zhou ◽  
Bavo Langerock ◽  
Corinne Vigouroux ◽  
Mahesh Kumar Sha ◽  
Michel Ramonet ◽  
...  
Keyword(s):  
Time Series ◽  
Indian Ocean ◽  
Mole Fraction ◽  
Seasonal Cycles ◽  
Reunion Island ◽  
Time Period ◽  
Réunion Island ◽  
The Indian Ocean ◽  
Good Agreement

Abstract. Atmospheric carbon monoxide (CO) and methane (CH4) mole fractions are measured by ground-based in situ cavity ring-down spectroscopy (CRDS) analyzers and Fourier transform infrared (FTIR) spectrometers at two sites (St Denis and Maïdo) on Reunion Island (21∘ S, 55∘ E) in the Indian Ocean. Currently, the FTIR Bruker IFS 125HR at St Denis records the direct solar spectra in the near-infrared range, contributing to the Total Carbon Column Observing Network (TCCON). The FTIR Bruker IFS 125HR at Maïdo records the direct solar spectra in the mid-infrared (MIR) range, contributing to the Network for the Detection of Atmospheric Composition Change (NDACC). In order to understand the atmospheric CO and CH4 variability on Reunion Island, the time series and seasonal cycles of CO and CH4 from in situ and FTIR (NDACC and TCCON) measurements are analyzed. Meanwhile, the difference between the in situ and FTIR measurements are discussed. The CO seasonal cycles observed from the in situ measurements at Maïdo and FTIR retrievals at both St Denis and Maïdo are in good agreement with a peak in September–November, primarily driven by the emissions from biomass burning in Africa and South America. The dry-air column averaged mole fraction of CO (XCO) derived from the FTIR MIR spectra (NDACC) is about 15.7 ppb larger than the CO mole fraction near the surface at Maïdo, because the air in the lower troposphere mainly comes from the Indian Ocean while the air in the middle and upper troposphere mainly comes from Africa and South America. The trend for CO on Reunion Island is unclear during the 2011–2017 period, and more data need to be collected to get a robust result. A very good agreement is observed in the tropospheric and stratospheric CH4 seasonal cycles between FTIR (NDACC and TCCON) measurements, and in situ and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) satellite measurements, respectively. In the troposphere, the CH4 mole fraction is high in August–September and low in December–January, which is due to the OH seasonal variation. In the stratosphere, the CH4 mole fraction has its maximum in March–April and its minimum in August–October, which is dominated by vertical transport. In addition, the different CH4 mole fractions between the in situ, NDACC and TCCON CH4 measurements in the troposphere are discussed, and all measurements are in good agreement with the GEOS-Chem model simulation. The trend of XCH4 is 7.6±0.4 ppb yr−1 from the TCCON measurements over the 2011 to 2017 time period, which is consistent with the CH4 trend of 7.4±0.5 ppb yr−1 from the in situ measurements for the same time period at St Denis.

scholarly journals Strong Intraseasonal Variability of Meridional Currents near 5°N in the Eastern Indian Ocean: Characteristics and Causes

2017 ◽  
Vol 47 (5) ◽  
pp. 979-998 ◽  
Author(s):  
Gengxin Chen ◽  
Weiqing Han ◽  
Yuanlong Li ◽  
Michael J. McPhaden ◽  
Ju Chen ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Rossby Waves ◽  
Intraseasonal Variability ◽  
Upper Ocean ◽  
Mean Flow ◽  
Eastern Boundary ◽  
Typical Period ◽  
The Indian Ocean ◽  
The Mean

AbstractThis paper reports on strong, intraseasonal, upper-ocean meridional currents observed in the Indian Ocean between the Bay of Bengal (BOB) and the equator and elucidates the underlying physical processes responsible for them. In situ measurements from a subsurface mooring at 5°N, 90.5°E reveal strong intraseasonal variability of the meridional current with an amplitude of ~0.4 m s−1 and a typical period of 30–50 days in the upper 150 m, which by far exceeds the magnitudes of the mean flow and seasonal cycle. Such prominent intraseasonal variability is, however, not seen in zonal current at the same location. Further analysis suggests that the observed intraseasonal flows are closely associated with westward-propagating eddylike sea surface height anomalies (SSHAs) along 5°N. The eddylike SSHAs are largely manifestations of symmetric Rossby waves, which result primarily from intraseasonal wind stress forcing in the equatorial waveguide and reflection of the equatorial Kelvin waves at the eastern boundary. Since the wave signals are generally symmetric about the equator, similar variability is also seen at 5°S but with weaker intensity because of the inclined coastline at the eastern boundary. The Rossby waves propagate westward, causing pronounced intraseasonal SSHA and meridional current in the upper ocean across the entire southern BOB between 84° and 94°E. They greatly weaken in the western Indian Basin, but zonal currents near the equator remain relatively strong.

Sign in / Sign up

Export Citation Format

Share Document