Pacific decadal oscillation causes fewer near-equatorial cyclones in the North Indian Ocean

Tropical cyclones do not form easily near the equator but can intensify rapidly, leaving little time for preparation. We investigate the number of near-equatorial (originating between 5°N and 11°N) tropical cyclones over the north Indian Ocean during post-monsoon season (October to December) over the past 60 years. The study reveals a marked 43% decline in the number of such cyclones in recent decades (1981-2010) compared to earlier (1951-1980). Here, we show this decline in tropical cyclone frequency is primarily due to the weakened low-level vorticity modulated by the Pacific Decadal Oscillation (PDO) and increased vertical wind shear. In the presence of low-latitude basin-wide warming and a favorable phase of the PDO, both the intensity and frequency of such cyclones are expected to increase. Such dramatic and unique changes in tropical cyclonic activity due to the interplay between natural variability and climate change call for appropriate planning and mitigation strategies.

Performance of high resolution (400 m) PM2.5 forecast over Delhi

This study reports a very high-resolution (400 m grid-spacing) operational air quality forecasting system developed to alert residents of Delhi and the National Capital Region (NCR) about forthcoming acute air pollution episodes. Such a high-resolution system has been developed for the first time and is evaluated during October 2019-February 2020. The system assimilates near real-time aerosol observations from in situ and space-borne platform in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to produce a 72-h forecast daily in a dynamical downscaling framework. The assimilation of aerosol optical depth and surface PM2.5 observations improves the initial condition for surface PM2.5 by about 45 µg/m3 (about 50%).The accuracy of the forecast degrades slightly with lead time as mean bias increase from + 2.5 µg/m3 on the first day to - 17 µg/m3 on the third day of forecast. Our forecast is found to be very skillful both for PM2.5 concentration and unhealthy/ very unhealthy air quality index categories, and has been helping the decision-makers in Delhi make informed decisions.

Characterization of atmospheric trace gases and water soluble inorganic chemical ions of PM1 and PM2.5 at Indira Gandhi International Airport, New Delhi during 2017-18 winter

Water soluble inorganic chemical ions of PM₁ and PM_2.5 and atmospheric trace gases were monitored simultaneously on hourly resolution at Indira Gandhi International Airport (IGIA), Delhi during 8 December 2017-10 February 2018. Monitoring was made by MARGA (Monitoring AeRosol and Gases in ambient Air) under winter fog experiment (WIFEX) program of the Ministry of Earth Sciences (MoES), Government of India. The result based on the analysis of the data so generated reveals that Cl^-, NH₄⁺, NO₃^- and SO₄^2- were dominant ions in order which collectively constituted 96.8 and 97.3% of the of the total measured ionic mass in PM₁ and PM_2.5 respectively. Their overall average concentrations in PM₁ were 19.5 ± 19.7, 18.4 ± 10.5, 16.6 ± 8.7 and 10.3 ± 5.7 μg/m³ and in PM_2.5 were 36.0 ± 33.9, 32.7 ± 17.2, 28.5 ± 13.6 and 19.9 ± 13.9 μg/m³. Average concentrations of HCl, HNO₃, HNO₂, SO₂ and NH₃ trace gases were 0.7 ± 0.3, 2.7 ± 1.1, 6.6 ± 4.7, 22.0 ± 12.3 and 25.7 ± 9.1 μg/m³ respectively. Weather parameters along with low mixing height played significant role in the occurrence of high concentration of these chemical species. NH₄⁺ was the prime neutralizer of the acidic components and mostly occurred in (NH₄)₂SO₄/NH₄HSO₄, NH₄NO₃ and NH₄Cl molecular forms. Major sources of these chemical species were fossil fuel combustion in aviation activity and transportation, coal burning in thermal power plants, industrial processes and emissions from biomass burning and agro-based activity. The quality of air with respect to PM_2.5 always remained deteriorated. It became alarming during low visibility period mainly due to high concentration of Cl^-, NO₃^-, SO₄^2- and NH₄⁺. Both meteorological and chemical processes interactively fed each other which occasionally resulted in fog development and visibility degradation. The knowledge gained by this study will help in simulation of atmospheric processes which lead to fog development and dispersal in the Delhi region.

Volatile organic compound measurements point to fog-induced biomass burning feedback to air quality in the megacity of Delhi

We report the first ambient measurements of thirteen VOCs for investigations of emissions and air quality during fog and non-fog wintertime conditions at a tower site (28.57° N, 77.11° E, 220 m amsl) in the megacity of Delhi. Measurements of acetonitrile (biomass burning (BB) tracer), isoprene (biogenic emission tracer in daytime), toluene (a traffic exhaust tracer) and benzene (emitted from BB and traffic), together with soluble and reactive oxygenated VOCs such as methanol, acetone and acetaldehyde were performed during the winters of 2015-16 and 2016-17, using proton transfer reaction mass spectrometry. Remarkably, ambient VOC composition changes during fog were not governed by solubility. Acetaldehyde, toluene, sum of C8-aromatics (e.g. xylenes), sum of C9-aromatics (e.g. trimethyl benzenes) decreased by ≥30% (>95% confidence interval), whereas acetonitrile and benzene showed significant increases by 20% (>70% confidence interval), even after accounting for boundary layer dilution. During fog, the lower temperatures appeared to induce an emissions feedback from enhanced open BB within Delhi for warming, releasing both gaseous and aerosol pollutants with consequences for fog chemistry, sustenance and intensity. The potential feedback is important to consider for improving current emission parametrizations in models used for predicting air quality and fog in such atmospheric environments.

Characterization and source identification of PM2.5 and its chemical and carbonaceous constituents during Winter Fog Experiment 2015-16 at Indira Gandhi International Airport, Delhi

Data on mass concentration of PM_2.5 and its carbonaceous and water soluble inorganic chemical ions were compiled through sampling of PM_2.5 at Indira Gandhi International Airport, Delhi during Dec. 16, 2015-Feb. 15, 2016 under Winter Fog Experiment (WIFEX) program of the Ministry of Earth Sciences (MoES) and analysing the samples. The data so generated were interpreted in terms of their variation on different time scales and apportioning their sources. It is found that mass concentration of PM_2.5 averaged over the whole period of observation was 198.6±55.6. The concentration of organic carbon (OC) and elemental carbon (EC) was 24.7±9.4 and 11.7±4.7μg/m³ respectively with no any trend of increase or decrease over the observational period. SO₄^2-, Cl^- and NO₃^- dominated over other anions with their overall average concentration 34.0±23.1, 32.7±16.1 and 13.3±8.7μg/m³ respectively. Among cations, NH₄⁺ showed highest concentration with an average value of 21.0±10.6μg/m³. Variation of daily average mass concentration of these parameters over the period of observation matched well with the variation of PM_2.5 mass concentration indicating thereby to be the major contributors to the PM_2.5 mass. NH₄⁺ mostly occurred as NH₄Cl and NH₄NO₃ and poorly as (NH₄)₂SO₄ or NH₄HSO₄. H⁺ ion mostly occurred as H₂SO₄ and occasionally as HNO₃. Carbonaceous aerosols and NO₃^- were mainly generated from fossil-fuel combustion. NH₄⁺ and anthropogenic Cl^- were mostly generated by biomass burning. The source of SO₄^2- was found to be industries and thermal power plants. Continental Ca²⁺ and Mg²⁺ originated from thermal power plants and soil dust.

Statistical Evidence for the Role of Southwestern Indian Ocean Heat Content in the Indian Summer Monsoon Rainfall

This study examines the benefit of using Ocean Mean Temperature (OMT) to aid in the prediction of the sign of Indian Summer Monsoon Rainfall (ISMR) anomalies. This is a statistical examination, rather than a process study. The thermal energy needed for maintaining and intensifying hurricanes and monsoons comes from the upper ocean, not just from the thin layer represented by sea surface temperature (SST) alone. Here, we show that the southwestern Indian OMT down to the depth of the 26 °C isotherm during January–March is a better qualitative predictor of the ISMR than SST. The success rate in predicting above- or below-average ISMR is 80% for OMT compared to 60% for SST. Other January–March mean climate indices (e.g., NINO3.4, Indian Ocean Dipole Mode Index, El Niño Southern Oscillation Modoki Index) have less predictability (52%, 48%, and 56%, respectively) than OMT percentage deviation (PD) (80%). Thus, OMT PD in the southwestern Indian Ocean provides a better qualitative prediction of ISMR by the end of March and indicates whether the ISMR will be above or below the climatological mean value.

A threefold rise in widespread extreme rain events over central India

Socioeconomic challenges continue to mount for half a billion residents of central India because of a decline in the total rainfall and a concurrent rise in the magnitude and frequency of extreme rainfall events. Alongside a weakening monsoon circulation, the locally available moisture and the frequency of moisture-laden depressions from the Bay of Bengal have also declined. Here we show that despite these negative trends, there is a threefold increase in widespread extreme rain events over central India during 1950-2015. The rise in these events is due to an increasing variability of the low-level monsoon westerlies over the Arabian Sea, driving surges of moisture supply, leading to extreme rainfall episodes across the entire central subcontinent. The homogeneity of these severe weather events and their association with the ocean temperatures underscores the potential predictability of these events by two-to-three weeks, which offers hope in mitigating their catastrophic impact on life, agriculture and property.Against the backdrop of a declining monsoon, the number of extreme rain events is on the rise over central India. Here the authors identify a threefold increase in widespread extreme rains over the region during 1950-2015, driven by an increasing variability of the low-level westerlies over the Arabian Sea.

Possible shift in the ENSO-Indian monsoon rainfall relationship under future global warming

EI Nino-Southern Oscillation (ENSO) and Indian monsoon rainfall are known to have an inverse relationship, which we have observed in the rainfall spectrum exhibiting a spectral dip in 3-5 y period band. It is well documented that El Nino events are known to be associated with deficit rainfall. Our analysis reveals that this spectral dip (3-5 y) is likely to shift to shorter periods (2.5-3 y) in future, suggesting a possible shift in the relationship between ENSO and monsoon rainfall. Spectral analysis of future climate projections by 20 Coupled Model Intercomparison project 5 (CMIP5) models are employed in order to corroborate our findings. Change in spectral dip speculates early occurrence of drought events in future due to multiple factors of global warming.

Reproducibility of alternative probe synthesis approaches for gene expression profiling with arrays

Before gene expression profiling with microarray technology can be transferred to the diagnostic setting, we must have alternative approaches for synthesizing probe from limited RNA samples, and we must understand the limits of reproducibility in interpreting gene expression results. The current gold standard of probes for use with both microarrays and high-density filter arrays are synthesized from 1 microg of purified poly(A)+ RNA. We evaluated two approaches for synthesizing cDNA probes from total RNA with subsequent hybridization to high-density filter arrays: 1) reverse transcription (RT) of 5 microg total RNA and 2) RT-polymerase chain reaction (RT-PCR) of 1 microg total RNA, using the SMART system. The reproducibility of these two approaches was compared to the current gold standard. All three methods were highly reproducible. Triplicate experiments resulted in the following concordance correlation coefficients to evaluate reproducibility: 0.88 for the gold standard, 0.86 for cDNA probe synthesized by RT from total RNA, and 0.96 for the SMART cDNA probe synthesized from total RNA. We also compared the expression profile of 588 genes for the total RNA methods to that obtained with the gold standard. Of 150 positive genes detected by the gold standard, 97 (65%) were detected by cDNA probe synthesized by RT of total RNA, and 122 (81%) were detected by the SMART cDNA probe. We conclude that SMART cDNA probe produces highly reproducible results and yields gene expression profiles that represent the majority of transcripts detected with the gold standard.