Interannual variability of the Indian Summer Monsoon Rainfall (ISMR) is modulated by Sea Surface Temperature (SST) anomalies over Indo-Pacific Oceans, especially by the El Niño Southern Oscillation ...(ENSO). In general, coupled models used for seasonal prediction overestimate the correlation between ENSO and ISMR compared to observations. By analysing the observational data from 1982 to 2017, this study shows that the relationship between ENSO and ISMR is weak during August compared to the other months of the summer monsoon season (June, July, and September). This weak association between ENSO and ISMR during August is due to an increase in the synoptic variability. Thus, the effect of large-scale flow dominated by ENSO is suppressed by the formation of a synoptic system in the Bay of Bengal (BoB), making ENSO-ISMR relation feeble in August. The data analysis of various coupled models shows that all models underestimate synoptic variability, due to which simulated ENSO-ISMR relation is overestimated during August. Coupled model exhibit strong biases in relative humidity and cyclonic circulation over the northern BoB hence underestimating the synoptic variability.
During the summer monsoon season, the Indian region experiences prominent south-westerly winds that extend up to the Philippines. These south-westerly winds encounter the Western Ghats (WG) and ...Deccan Plateau (DP). Many studies have discussed the role of WG in modulating the monsoon flow, convection and rainfall over the Indian region. However, the orographic influence of south-west orography (DP and WG both) on large-scale monsoon circulation remains unexplored. An experimental global model simulation was conducted with removed DP and WG orography to investigate this. The results showed that modifying the orography can alter the wind flow across the Philippines, Western North Pacific, and Bay of Bengal, leading to mid-tropospheric heating changes due to the monsoon trough position over these regions. This change in the monsoon trough position results in the stationary Rossby wave. The stationary Rossby wave generated strengthened winds over the south Bay of Bengal (BoB), which merges with the Philippine anticyclone over the Western North Pacific. The dynamical and thermodynamical changes are observed near Western North Pacific. Consequently, there is an increase in rainfall over the Western North Pacific and a decrease in rainfall over India. This study also found that the change in the monsoon flow affects the low-pressure systems and tropical cyclones. This work highlights how the South-West Indian orography affects the monsoon flow and synoptic variability across India, the West North Pacific, and the Philippines anticyclone. Thus, understanding the monsoon flow over the orography will help understand the dynamics.
Present study analyses the role of tropical Pacific sea surface temperature (SST) biases in simulating the mean and inter-annual variability of Indian summer monsoon rainfall (ISMR) using the ...hindcasts from Monsoon Mission CFSv2 (MMCFS) and ECMWF-SYSTEM4 (ES4) prediction systems. ES4 simulates the mean and annual cycle of ISMR better than MMCFS when initialized with February initial conditions (3-month lead, Feb IC). At the same time, interannual variability (IAV) and skill (correlation between the ensemble mean hindcast and observations) are the highest (least) for MMCFS (ES4). May IC (0-month lead) hindcasts of both the models have similar mean, annual cycle, IAV and skill. Further analysis shows that ES4_Feb IC hindcasts exhibit a strong cold bias (~ 2 °C) in the equatorial central Pacific, which is close to zero for MMCFS_Feb IC. Meanwhile, the 0-month lead (May IC) hindcast has a similar cold bias (~ 1.5 °C) in the equatorial Pacific for both the model hindcasts. Thus, model hindcasts with a better mean ISMR are having a strong cold bias in the equatorial Pacific and that having very less SST bias has higher IAV and skill for ISMR simulations. Additional investigation using North American National Multi-Model Ensemble Project (NMME) models is carried out and the following conclusion on the different roles of Pacific mean state bias is drawn. Hindcasts with strong cold SST bias in the tropical Pacific (ES4 hindcast and May IC hindcasts of MMCFS) tend to mimic the teleconnections associated with La Nina conditions reducing the dry bias over India, resulting in mean ISMR closer to the observed value, still less than the observed mean. At the same time, due to the same strong cold bias, the El Nino-Southern Oscillation (ENSO) induced rainfall and circulation pattern in the Pacific are weak and extended further northwestward. This weakens the ENSO induced heat sources over the Indian Ocean and monsoon region, resulting in reduced ENSO-ISMR teleconnections. These factors result in a poor simulation of interannual variability and skill of ISMR. On the other hand, model hindcasts with less cold bias in the equatorial Pacific (MMCFS_Feb IC) suffer from strong dry bias over India; however, the skill of ISMR is higher as a result of strong ENSO-Monsoon teleconnections. Thus the study confirms the differential role of SST bias in the tropical Pacific in simulating mean and IAV of ISMR in seasonal prediction models. A close to observed mean SST in the tropical Pacific and proper ENSO-Monsoon teleconnection is essential for the better skill of ISMR in the present generation seasonal prediction models.
MONSOON MISSION Rao, Suryachandra A.; Goswami, B. N.; Sahai, A. K. ...
Bulletin of the American Meteorological Society,
12/2019, Letnik:
100, Številka:
12
Journal Article
Recenzirano
Odprti dostop
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.
The present study assess the potential predictability of boreal summer (June through September, JJAS) tropical sea surface temperature (SST) and Indian summer monsoon rainfall (ISMR) using high ...resolution climate forecast system (CFSv2-T382) hindcasts. Potential predictability is computed using relative entropy (RE), which is the combined effect of signal strength and model spread, while the correlation between ensemble mean and observations represents the actual skill. Both actual and potential skills increase as lead time decreases for Niño3 index and equatorial East Indian Ocean (EEIO) SST anomaly and both the skills are close to each other for May IC hindcasts at zero lead. At the same time the actual skill of ISMR and El Niño Modoki index (EMI) are close to potential skill for Feb IC hindcasts (3 month lead). It is interesting to note that, both actual and potential skills are nearly equal, when RE has maximum contribution to individual year’s prediction skill and its relationship with absolute error is insignificant or out of phase. The major contribution to potential predictability is from ensemble mean and the role of ensemble spread is limited for Pacific SST and ISMR hindcasts. RE values are able to capture the predictability contribution from both initial SST and simultaneous boundary forcing better than ensemble mean, resulting in higher potential skill compared to actual skill for all ICs. For Feb IC hindcasts at 3 month lead time, initial month SST (Feb SST) has important predictive component for El Niño Modoki and ISMR leading to higher value of actual skill which is close to potential skill. This study points out that even though the simultaneous relationship between ensemble mean ISMR and global SST is similar for all ICs, the predictive component from initial SST anomalies are captured well by Feb IC (3 month lead) hindcasts only. This resulted in better skill of ISMR for Feb IC (3 month lead) hindcasts compared to May IC (0 month lead) hindcasts. Lack of proper contribution from initial SST and teleconnections induces large absolute error for ISMR in May IC hindcasts resulting in very low actual skill. Thus the use of potential predictability skill and actual skill collectively help to understand the fidelity of the model for further improvement by differentiating the role of initial SST and simultaneous boundary forcing to some extent.
Interannual variability of the Indian Summer Monsoon Rainfall (ISMR) is modulated by Sea Surface Temperature (SST) anomalies over Indo-Pacific Oceans, especially by the El Niño Southern Oscillation ...(ENSO). In general, coupled models used for seasonal prediction overestimate the correlation between ENSO and ISMR compared to observations. By analysing the observational data from 1982 to 2017, this study shows that the relationship between ENSO and ISMR is weak during August compared to the other months of the summer monsoon season (June, July, and September). This weak association between ENSO and ISMR during August is due to an increase in the synoptic variability. Thus, the effect of large-scale flow dominated by ENSO is suppressed by the formation of a synoptic system in the Bay of Bengal (BoB), making ENSO-ISMR relation feeble in August. The data analysis of various coupled models shows that all models underestimate synoptic variability, due to which simulated ENSO-ISMR relation is overestimated during August. Coupled model exhibit strong biases in relative humidity and cyclonic circulation over the northern BoB hence underestimating the synoptic variability.
Extracellular enzymes produced from
Streptomyces
have the potential to replace toxic chemicals that are being used in various industries. The endorsement of this replacement has not received a better ...platform in developing countries. In this review, we have discussed the impact of chemicals and conventional practices on environmental health, and the role of extracellular enzymes to replace these practices. Burning of fossil fuels and agriculture residue is a global issue, but the production of biofuel using extracellular enzymes may be the single key to solve all these issues. We have discussed the replacement of hazardous chemicals with the use of xylanase, cellulase, and pectinase in food industries. In paper industries, delignification was done by the chemical treatment, but xylanase and laccase have the efficient potential to remove the lignin from pulp. In textile industries, the conventional method includes the chemicals which affect the nervous system and other organs. The use of xylanase, cellulase, and pectinase in different processes can give a safe and environment-friendly option to textile industries. Hazardous chemical pesticides can be replaced by the use of chitinase as an insecticide and fungicide in agricultural practices.
Abstract
Ionic covalent organic frameworks (iCOFs) are new examples of porous materials and have shown great potential for various applications. When functionalized with suitable emission sites, ...guest uptake via the ionic moieties of iCOFs can cause a significant change in luminescence, making them excellent candidates for chemosensors. In here, we present a luminescence sensor in the form of an ionic covalent organic framework (TGH
+
•PD) composed of guanidinium and phenanthroline moieties for the detection of ammonia and primary aliphatic amines. TGH
+
•PD exhibits strong emission enhancement in the presence of selective primary amines due to the suppression of intramolecular charge transfer (ICT) with an ultra-low detection limit of 1.2 × 10
‒7
M for ammonia. The presence of ionic moieties makes TGH
+
•PD highly dispersible in water, while deprotonation of the guanidinium moiety by amines restricts its ICT process and signals their presence by enhanced fluorescence emission. The presence of ordered pore walls introduces size selectivity among analyte molecules, and the iCOF has been successfully used to monitor meat products that release biogenic amine vapors upon decomposition due to improper storage.
Hotspot engineering has the potential to transform the field of surface-enhanced Raman spectroscopy (SERS) by enabling ultrasensitive and reproducible detection of analytes. However, the ability to ...controllably generate SERS hotspots, with desired location and geometry, over large-area substrates, has remained elusive. In this study, we sculpt artificial edges in monolayer molybdenum disulfide (MoS2) by low-power focused laser-cutting. We find that when gold nanoparticles (AuNPs) are deposited on MoS2 by drop-casting, the AuNPs tend to accumulate predominantly along the artificial edges. First-principles density functional theory (DFT) calculations indicate strong binding of AuNPs with the artificial edges due to dangling bonds that are ubiquitous on the unpassivated (laser-cut) edges. The dense accumulation of AuNPs along the artificial edges intensifies plasmonic effects in these regions, creating hotspots exclusively along the artificial edges. DFT further indicates that adsorption of AuNPs along the artificial edges prompts a transition from semiconducting to metallic behavior, which can further intensify the plasmonic effect along the artificial edges. These effects are observed exclusively for the sculpted (i.e., cut) edges and not observed for the MoS2 surface (away from the cut edges) or along the natural (passivated) edges of the MoS2 sheet. To demonstrate the practical utility of this concept, we use our substrate to detect Rhodamine B (RhB) with a large SERS enhancement (∼104) at the hotspots for RhB concentrations as low as ∼10–10 M. The single-step laser-etching process reported here can be used to controllably generate arrays of SERS hotspots. As such, this concept offers several advantages over previously reported SERS substrates that rely on electrochemical deposition, e-beam lithography, nanoimprinting, or photolithography. Whereas we have focused our study on MoS2, this concept could, in principle, be extended to a variety of 2D material platforms.
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