Sabba Syal Elahi Interview (1 of 2)

Bio: Sabba Syal Elahi received her M.F.A. from the School of the Art Institute of Chicago, and her art has been featured nationally at ArtWallah, internationally in Spain and Pakistan, and in the Chicagoland area. Sabba’s artwork is rooted in her bicultural experience and explores issues of cultural and historical representation, identity, and gender through personal, family, and community narratives. From 2011-2009 Sabba curated the visual art for an annual Chicago event called Voices of Resistance, which showcased the work of Chicago and Midwest based South Asian artists. Sabba has served four years as Coordinator of College and Career Programs at Marwen, a position which complements her psychology and visual arts background and professional experience serving youth, families, and communities of color. Recently, Sabba participated in a Teaching Artist Residency at Ragdale and will begin the Bolt Artist Residency program in July of 2013

How accurate are satellite estimates of precipitation over the north Indian Ocean?

Following the launch of the Global Precipitation Measurement (GPM) Core Observatory in early 2014, motivated from the successful Tropical Rainfall Measurement Mission (TRMM) satellite, an advanced and sophisticated global multi-satellite precipitation product – Integrated Multi- satellitE Retrievals for GPM (IMERG) was released at finer spatio-temporal scales. This precipitation product has been upgraded recently after several refinements and supposed to be superior to other existing global or quasi-global multi-satellite precipitation estimates. In the present study, IMERG precipitation is comprehensively evaluated for the first time against moored buoy observations over the north Indian Ocean at hourly scale for the study period of March 2014 to December 2015. IMERG precipitation performs considerably better over the Bay of Bengal than the Arabian Sea in both detection and estimation. The systematic error in IMERG is appreciably lower by about 14%, however, it generally overestimates in-situ precipitation and also exhibits noticeable false alarms. Furthermore, IMERG essentially shows an improvement over the TRMM Multi-satellite Precipitation Analysis (TMPA) at a daily scale over the north Indian Ocean. IMERG precipitation estimates show overall promising error characteristics, but there is still a need of substantial efforts for improvement in the satellite-based precipitation estimation algorithms especially over data sparse regions such as north Indian Ocean

Air-sea interaction in the Bay of Bengal

Author Posting. © The Oceanography Society, 2016. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 29, no. 2 (2016): 28–37, doi:10.5670/oceanog.2016.36.Recent observations of surface meteorology and exchanges of heat, freshwater, and momentum between the ocean and the atmosphere in the Bay of Bengal are presented. These observations characterize air-sea interaction at 18°N, 89.5°E from December 2014 to January 2016 and also at other locations in the northern Bay of Bengal. Monsoonal variability dominated the records, with winds to the northeast in summer and to the southwest in winter. This variability included a strong annual cycle in the atmospheric forcing of the ocean in the Bay of Bengal, with the winter monsoon marked by sustained ocean heat loss resulting in ocean cooling, and the summer monsoon marked by strong storm events with dark skies and rain that also resulted in ocean cooling. The spring intermonsoon was a period of clear skies and low winds, when strong solar heating and weak wind-driven mixing led to ocean warming. The fall intermonsoon was a transitional period, with some storm events but also with enough clear skies and sunlight that ocean surface temperature rose again. Mooring and shipboard observations are used to examine the ability of model-based surface fluxes to represent air-sea interaction in the Bay of Bengal; the model-based fluxes have significant errors. The surface forcing observed at 18°N is also used together with a one-dimensional ocean model to illustrate the potential for local air-sea interaction to drive upper-ocean variability in the Bay of Bengal.Deployment of the WHOI mooring and R. Weller and J.T. Farrar were supported by the US Office of Naval Research, grant N00014-13-1-0453. N. Suresh Kumar and B. Praveen Kumar acknowledge the financial support from Ministry of Earth Sciences (MoES, Government of India)

US Cosmic Visions: New Ideas in Dark Matter 2017: Community Report

This white paper summarizes the workshop "U.S. Cosmic Visions: New Ideas in Dark Matter" held at University of Maryland on March 23-25, 2017.Comment: 102 pages + reference

Phytoplankton bloom in the Bay of Bengal during the northeast monsoon and its intensification by cyclones

[1] Satellite derived chlorophyll a imageries are used to present a phytoplankton bloom in the Bay of Bengal during the northeast monsoon (November-February) and the mechanisms that can upwell nutrients to sustain the bloom are investigated using sea level anomalies and winds. OCTS and SeaWiFS chlorophyll a images show that there is a phytoplankton bloom in the southwestern part of the bay during November-January. The chlorophyll a concentration of the bloom can be as high as 2 mg m(-3) compared to near zero value before the bloom. Open ocean upwelling driven by Ekman pumping causes the bloom. The cyclones which are common during this period lead to localized intense blooms in the western Bay of Bengal. The offshore extent and the intensity of the bloom varies from year to year. The bloom was absent during 1997 due to weak Ekman pumping

Phytoplankton bloom in the Bay of Bengal during the Northeast monsoon and its intensification by cyclones

Satellite derived chlorophyll a imageries are used to present a phytoplankton bloom in the Bay of Bengal during the northeast monsoon (November-February) and the mechanisms that can upwell nutrients to sustain the bloom are investigated using sea level anomalies and winds. OCTS and SeaWiFS chlorophyll a images show that there is a phytoplankton bloom in the southwestern part of the bay during November-January. The chlorophyll a concentration of the bloom can be as high as 2 mg m<SUP>−3</SUP> compared to near zero value before the bloom. Open ocean upwelling driven by Ekman pumping causes the bloom. The cyclones which are common during this period lead to localized intense blooms in the western Bay of Bengal. The offshore extent and the intensity of the bloom varies from year to year. The bloom was absent during 1997 due to weak Ekman pumping

How accurate are satellite estimates of precipitation over the north Indian Ocean?

Following the launch of the Global Precipitation Measurement (GPM) Core Observatory in early 2014, motivated from the successful Tropical Rainfall Measurement Mission (TRMM) satellite, an advanced and sophisticated global multi-satellite precipitation product-Integrated Multi-satellitE Retrievals for GPM (IMERG) was released at finer spatio-temporal scales. This precipitation product has been upgraded recently after several refinements and supposed to be superior to other existing global or quasi-global multi-satellite precipitation estimates. In the present study, IMERG precipitation is comprehensively evaluated for the first time against moored buoy observations over the north Indian Ocean at hourly scale for the study period of March 2014 to December 2015. IMERG precipitation performs considerably better over the Bay of Bengal than the Arabian Sea in both detection and estimation. The systematic error in IMERG is appreciably lower by about 14%; however, it generally overestimates in-situ precipitation and also exhibits noticeable false alarms. Furthermore, IMERG essentially shows an improvement over the TRMM Multi-satellite Precipitation Analysis (TMPA) at a daily scale over the north Indian Ocean. IMERG precipitation estimates show overall promising error characteristics, but there is still a need of substantial efforts for improvement in the satellite-based precipitation estimation algorithms especially over data sparse regions such as north Indian Ocean

Mechanisms of summer intraseasonal sea surface temperature oscillations in the Bay of Bengal

Intraseasonal variations (ISV) of sea surface temperature (SST) in the Bay of Bengal (BoB) is highest in its northwestern part. An Indian Ocean model forced by QuikSCAT winds and climatological river discharge (QR run) reproduces ISV of SST, albeit with weaker magnitude. Air-sea fluxes, in the presence of a shallow mixed layer, efficiently effect intraseasonal SST fluctuations. Warming during intraseasonal events is smaller (<1°C) for June - July period and larger (1.5° to 2°C) during September, the latter due to a thinner mixed layer. To examine the effect of salinity on ISV, the model was run by artificially increasing the salinity (NORR run) and by decreasing it (MAHA10 run). In NORR, both rainfall and river discharge were switched off and in MAHA10 the discharge by river Mahanadi was increased tenfold. The spatial pattern of ISV as well as its periodicity was similar in QR, NORR and MAHA10. The ISV was stronger in NORR and weaker in MAHA10, compared to QR. In NORR, both intraseasonal warming and cooling were higher than in QR, the former due to reduced air-sea heat loss as the mean SST was lower, and the latter due to enhanced subsurface processes resulting from weaker stratification. In MAHA10, both warming and cooling were lower than in QR, the former due to higher air-sea heat loss owing to higher mean SST, and the latter due to weak subsurface processes resulting from stronger stratification. These model experiments suggest that salinity effects are crucial in determining amplitudes of intraseasonal SST variations in the BoB