An optimum initial manifold for improved skill and lead in long-range forecasting of monsoon variability
by K. C. Gouda, S. Joshi & Nagaraj Bhat
Using an initial manifold approach, an ensemble forecast methodology is shown to simultaneously increase lead and realizable skill in long-range forecasting of monsoon over continental India. Initial manifold approach distinguishes the initial states that have coherence from a collection of unrelated states. In this work, an optimized and validated variable resolution general circulation model is being adopted for long-range forecasting of monsoon using the multi-lead ensemble methodology. In terms of realizable skill (as against potential) at resolution (~60km) and lead (2–5 months) considered here, the present method performs very well. The skill of the improved methodology is significant, capturing 9 of the 12 extreme years of monsoon during 1980–2003 in seasonal (June–August) scale. Eight-member ensemble-average hindcasts carried out for realizable skill with lead of 2 (for June) to 5 (for August) months and an optimum ensemble is presented.
Source: https://doi.org/10.1007/s00704-021-03589-x and https://link.springer.com/article/10.1007/s00704-021-03589-x
High‐resolution climate change projection of northeast monsoon rainfall over peninsular India
by Jayasankar C B, K Rajendran, Sajani Surendran and K V Ajay Anand
In this study, projected changes in mean northeast monsoon (NEM) rainfall and associated extreme rainfall and temperature events, over peninsular India (PI) and its six subdivisions, are quantified. High‐resolution dynamically downscaled simulations of the Weather Research and Forecasting (WRF) regional climate model driven by the boundary conditions from the Community Climate System Model version 4 (CCSM4) model (WRF‐CCSM4) are compared with statistically downscaled simulations of NASA Earth Exchange Global Daily Downscaled Projections (NEX‐GDDP). Over PI, these downscaled simulations show low bias in mean NEM rainfall (≤ − 0.44 mm·day−1) and high pattern correlation coefficient (≥0.75), giving confidence in their future projections. Under future warming over PI, both downscaled simulations project future significant enhancement in NEM rainfall with WRF‐CCSM4 projecting 1.98 mm·day−1 (83.78% change with respect to the present‐day mean) whereas the multimodel ensemble (MME) of eight NEX‐GDDP models project 0.67 ± 0.58 mm·day−1 (19.78%) by the middle of the century and 1.42 ± 0.97 mm·day−1 (42.76%) by the end of the century. Analysis of extreme rainfall events shows that WRF‐CCSM4 projects future enhancement (reduction) in extreme rainfall (R95p) days over 91.4% (8.6%) of grid‐points over PI. In future, coastal areas of Karnataka and Andhra Pradesh will likely experience increased extreme rainfall occurrence by more than 25 days and 15–20 days respectively. Projected future enhancement in the mean and extreme NEM rainfall is attributed to the increased precipitable water under a warming climate. Future projection of extreme temperature indices shows an increase in minimum and maximum temperatures over PI during the NEM season. Over PI, future winter nights and days are found to be warmer than those in the present day and the temperature change in future winter nights is found to be larger than that in winter days. This climate change information would help decision‐makers in evaluating existing policies and devising revised policies to reduce risk due to climate change.
Citation: Jayasankar C B, K Rajendran, Sajani Surendran and K V Ajay Anand 2021: High-resolution Climate Change Projection of Northeast Monsoon Rainfall over Peninsular India.Quarterly Journal of Royal Meteorological Society, doi: 10.1002/qj.4017
Source:https://doi.org/10.1002/qj.4017
Evaluation of the Skill of a Fully-Coupled Atmospheric–Hydrological Model in Simulating Extreme Hydrometeorological Event: A Case Study Over Cauvery River Catchment
by Sumana Sarkar & S. Himesh
The monsoon-driven river basins are more vulnerable to the flash-floods triggered by intense rainfall activities. Due to the lack of adequate high resolution forecast of real-time hydro-meteorological variables, a reliable forecast of flash floods remains a challenge. One plausible way to generate such a high-resolution forecast of hydro-meteorological variables is to use a coupled atmospheric–hydrologic modelling system. Thus, in this study, a physically-based, fully distributed, multi-scale hydrologic modelling framework, WRF-Hydro with optimized configurations (stand-alone and coupled-mode) is used to simulate the important hydro-meteorological variables like precipitation, runoff, soil moisture, and land surface heat fluxes over Cauvery river basin, India. In stand-alone mode, the model is driven by the high-resolution gridded data from the Global Land Data Assimilation System; while the coupled model is run with the WRF atmospheric model. In this study, the ability of a fully coupled WRF–WRF-Hydro modelling framework , with 3 km grid spacing is used to simulate the hydro-meteorological conditions during an extreme rainfall event (08–09 August 2019). The innermost domain of WRF-Hydro in conjunction with a high resolution hydrological routing grid (300 m) is also utilized, to include the subgrid scale disaggregation–aggregation weighting procedures to generate the land–atmospheric feedbacks on the hydrometeorological variables. The resulting variables have been validated through relevant observations; the overall performance of the coupled WRF-Hydro is shown to be relatively good when compared to the WRF-only simulations.
Source: https://doi.org/10.1007/s00024-021-02684-4
Insights from a Pan India Sero-Epidemiological survey (Phenome-India Cohort) for SARS-CoV2
by Salwa Naushin, Viren Sardana, Rajat Ujjainiya, Nitin Bhatheja, Rintu Kutum, Akash Kumar Bhaskar, Shalini Pradhan, Satyartha Prakash, Raju Khan, Birendra Singh Rawat, Karthik Bharadwaj Tallapaka, Mahesh Anumalla, Giriraj Ratan Chandak, Amit Lahiri, Susanta Kar, Shrikant Ramesh Mulay, Madhav Nilakanth Mugale, Mrigank Srivastava, Shaziya Khan, Anjali Srivastava, Bhawna Tomar, Murugan Veerapandian, Ganesh Venkatachalam, Selvamani Raja Vijayakumar, Ajay Agarwal, Dinesh Gupta, Prakash M Halami, Muthukumar Serva Peddha, Gopinath M Sundaram, Ravindra P Veeranna, Anirban Pal, Vinay Kumar Agarwal, Anil Ku Maurya, Ran Vijay Kumar Singh, Ashok Kumar Raman, Suresh Kumar Anandasadagopan, Parimala Karuppanan, Subramanian Venkatesan, Harish Kumar Sardana, Anamika Kothari, Rishabh Jain, Anupma Thakur, Devendra Singh Parihar, Anas Saifi, Jasleen Kaur, Virendra Kumar, Avinash Mishra, Iranna Gogeri, Geethavani Rayasam,
On the build-up of dust aerosols and possible indirect effect during Indian summer monsoon break spells using recent satellite observations of aerosols and cloud properties
by Arya V. B., Sajani Surendran and Kavirajan Rajendran
Abstract
Association of higher (lower) rainfall with lower (higher) Aerosol Optical Depth (AOD) is consistent with the understanding that increased washout (build-up) and shorter (longer) life-time of aerosols occur in wetter (drier) conditions. Given the life-time of aerosols, it is imperative to examine how aerosols impact active/break (wetter/drier than normal) spells, the prominent intraseasonal variability (ISV) of Indian summer monsoon (ISM), through their composite analysis using recent satellite observations of aerosols and cloud properties, circulation and rainfall. Dust aerosols can act as CCN and participate efficiently in cloud processes during active phase. During breaks, build-up of desert dust transported by prevalent circulation, is associated with lower cloud effective radius implying aerosols’ indirect effect where they can inhibit cloud growth in the presence of reduced moisture and decrease precipitation efficiency/rainfall. Correspondingly, correlation albeit small, between intraseasonal anomalies of AOD and rainfall is negative, when AOD leads rainfall by 3–5 days implying that indirect aerosols impact is effective during breaks, though it is not the dominant responsible factor. During breaks, lower shortwave flux at top of atmosphere hints at dust-induced semi-direct effect. As breaks are permanent features of ISM, incorporation of dust-induced feedbacks in models, is essential for improved ISV simulation and ISM prediction.
Citation: Arya V. B., Sajani Surendran and Kavirajan Rajendran. On the build-up of dust aerosols and possible indirect effect during Indian summer monsoon break spells using recent satellite observations of aerosols and cloud properties. J. Earth Syst. Sci., 130, 42 (2021).
- Evaluating the Spatial Distribution of WRF-Simulated Rainfall, 2-m Air Temperature, and 2-m Relative Humidity over the Urban Region of Bangalore, India
- Seasonal horizontal deformations obtained using GPS and GRACE data: case study of North-East India and Nepal Himalaya
- Data sequence signal manipulation in multipath TCP (MPTCP): The vulnerability, attack and its detection
- Revisiting the seismogenic characteristics of stable continental interiors: The case of three Indian events
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