In spite of the summer monsoon’s importance in determining the life and economy of an agriculture-dependent country like India, committed efforts toward improving its prediction and simulation have been limited. Hence, a focused mission mode program Monsoon Mission (MM) was founded in 2012 to spur progress in this direction. This article explains the efforts made by the Earth System Science Organization (ESSO), Ministry of Earth Sciences (MoES), Government of India, in implementing MM to develop a dynamical prediction framework to improve monsoon prediction. Climate Forecast System, version 2 (CFSv2), and the Met Office Unified Model (UM) were chosen as the base models. The efforts in this program have resulted in 1) unparalleled skill of 0.63 for seasonal prediction of the Indian monsoon (for the period 1981–2010) in a high-resolution (∼38 km) seasonal prediction system, relative to present-generation seasonal prediction models; 2) extended-range predictions by a CFS-based grand multimodel ensemble (MME) prediction system; and 3) a gain of 2-day lead time from very high-resolution (12.5 km) Global Forecast System (GFS)-based short-range predictions up to 10 days. These prediction skills are on par with other global leading weather and climate centers, and are better in some areas. Several developmental activities like coupled data assimilation, changes in convective parameterization, cloud microphysics schemes, and parameterization of land surface processes (including snow and sea ice) led to the improvements such as reducing the strong model biases in the Indian summer monsoon simulation and elsewhere in the tropics.

Judicious combination of fluorescence and magnetic properties along with ample drug loading capacity and control release property remains a key challenge in the design of nanotheranostic agents. This paper reports the synthesis of highly hydrophilic optically traceable mesoporous carbon nanospheres which can sustain payloads of the anticancer drug doxorubicin and T2 contrast agent such as cobalt ferrite nanoparticles. The luminescent magnetic hybrid system has been prepared on a mesoporous silica template using a resorcinol-formaldehyde precursor. The mesoporous matrix shows controlled release of the aromatic drug doxorubicin due to disruption of supramolecular π-π interaction at acidic pH. The particles show MR contrast behavior by affecting the proton relaxation with transverse relaxivity (r2) 380 mM(-1) S(-1). The multicolored emission and upconversion luminescence property of our sample are advantageous in bioimaging. In vitro cell experiments shows that the hybrid nanoparticles are endocyted by the tumor cells through passive targeting. The pH-responsive release of doxorubicin presents chemotherapeutic inhibition of cell growth through induction of apoptosis.

Graphical abstractA water dispersible magnetic nanoparticle and carbon quantum dot based sensor has been designed by a simple technique. The nanosensor is highly selective and sensitive towards fluoride ion in aqueous solution and intracellular environment.ABSTRACT:A robust reusable fluoride sensor comprising of a receptor in charge of the chemical recognition and a fluorophore responsible for signal recognition has been designed.Highly fluorescent carbon quantum dot (CD) and magnetically separable nickel ethylenediaminetetraacetic acid (EDTA) complex bound-silica coated magnetite nanoparticle (Fe 3 O 4 @SiO 2 -EDTA-Ni) have been used as fluorophore and fluoride ion receptor respectively.The assay is based on the exchange reaction between the CD and F -, which persuades the binding of fluoride to magnetic receptor. This method is highly sensitive, fast and selective for fluoride ion in aqueous solution. The linear response range of fluoride (R 2 = 0.992) was found to be 1 to 20 µM with a minimum detection limit of 0.06 µM. Excellent magnetic property as well as superparamagnetic nature of the receptor are advantageous for the removal and well quantification of fluoride ion. The practical utility of the method is well tested with tap water.Due to high sensitivity, reusability, effectivity and biocompatibility, it exhibits great promise as a fluorescent probe for intracellular detection of fluoride.

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Typhoons are considered as one of the most powerful disaster-spawning weather phenomena. Recent studies have revealed that typhoons will be stronger and more powerful in a future warmer climate and be a threat to lives and properties. In this study, we conduct downscaling experiments of an extreme rain-producing typhoon, Typhoon Lionrock (2016), to assess the impacts of climate change on resulting hazards by assuming pseudo global warming (PGW) conditions. The downscaled precipitations over the landfall region in the present climate condition agree well with the Radar-Automated Meteorological Data Acquisition System (Radar-AMeDAS) observations. A typhoon track in the future climate similar to that in the present climate is successfully reproduced, with a stronger wind speed (by ~ 20 knots) and lower central pressure (by ~ 20 hPa) under the PGW condition. The changes in precipitation amounts associated with the typhoon under PGW condition are analyzed over seven individual prefectures in the northern part of Japan. The typhoon in the warming climate produces more precipitation over all prefectures. Iwate, Aomori, Akita, Miyagi, and Hokkaido are projected to have relatively more precipitation associated with the typhoon in the warming climate. The overall analysis suggests that Typhoon Lionrock under PGW may increase the risk of flooding, damages to infrastructures, and lives staying along the typhoon track.