Comparison of the Performance of Hybrid ETKF-3DVAR and 3DVAR Data Assimilation Systems on Short-Range Forecasts during Indian Summer Monsoon Season in a Limited-Area Model
by Rekha Bharali Gogoi, Govindan Kutty, V. Rakesh & Arup Borogain
The impact of deploying a flow-dependent ensemble error covariance in Weather Research and Forecasting (WRF) three-dimensional variational (3DVAR) data assimilation (DA) system is examined for short-range rainfall forecasts during an Indian summer monsoon season. The flow-dependent background error covariance (BEC) is generated using a 50-member ensemble, which is further updated using the ensemble transform Kalman filter (ETKF). Assimilation is performed using a Hybrid variational-ensemble (“Hybrid”) and traditional 3DVAR DA system during the 4 weeks of July 2013. The forecasted wind, temperature, and rainfall from the assimilation experiments are verified against corresponding observations. The results indicate that the flow-dependent ensemble background error covariance in 3DVAR has systematically improved the forecasted wind and temperature when compared to the traditional 3DVAR. Similarly, rainfall forecast skill is superior in the Hybrid experiments relative to that of 3DVAR. Convection-permitting resolution rainfall forecast is validated against 746 telemetric rain gauge observations over the state of Karnataka. The Hybrid experiments show higher quantitative precipitation forecast skill than 3DVAR, particularly towards the later stages of data assimilation cycling. Spatially, the 3DVAR experiment shows a dry bias over the upper peninsular regions and a slight wet bias over the central and the northern Indian regions, while the magnitude of such wet and dry biases is smaller in forecasts from Hybrid analysis. Additionally, the westerly wind over the peninsular Indian landmass analyzed by 3DVAR is considerably weaker than that analyzed by the Hybrid experiments. This is proposed as a possible reason for the reduced dry bias in rainfall forecasts over the Indian landmass in Hybrid versus 3DVAR experiments.
Source: https://link.springer.com/article/10.1007/s00024-020-02537-6
Dengue situation in India: Suitability and transmission potential model for present and projected climate change scenarios
by Satya Ganesh Kakarla, Kantha Rao Bhimala, Madhusudhan Rao Kadiri, Sriram Kumaraswamy and Srinivasa Rao Mutheneni
Abstract: Dengue fever is mosquito borne viral disease caused by dengue virus and transmitted by Aedes mosquitoes. In recent years the dengue has spread rapidly to several regions and it becomes a major public health menace globally. Dengue transmission is strongly influenced by environmental factors such as temperature and rainfall. In the present study, a climate driven dengue model was developed and predicted areas vulnerable for dengue transmission under the present and future climate change scenarios in India. The study also projected the dengue distribution risk map using representative concentration pathways (RCP4.5 and RCP8.5) in India in 2018–2030 (forthcoming period), 2031–2050 (intermediate period) and 2051–2080 (long period).
The dengue cases assessed in India from 1998 to 2018 and found that the dengue transmission is gradually increasing year over year. The temperature data from 1980 to 2017 shows that, the mean temperatures are raising in the Southern region of India. During 2000–2017 periods the dengue transmission is steadily increasing across the India in compare with 1980–1999 periods. The dengue distribution risk is predicted and it is revealed that the coastal states have yearlong transmission possibility, but the high transmission potential is observed throughout the monsoon period. Due to the climate change, the expansion two more months of dengue transmission risk occurs in many regions of India. Both RCP4.5 and RCP8.5 scenarios revealed that dengue outbreaks might occur at larger volume in Southern, Eastern, and Central regions of India. Furthermore a sensitivity analysis was performed to explore the impact of climate change on dengue transmission. These results helps to suggest appropriate control measures should be implemented to limit the spread in future warmer climates. Besides these, a proper plan is required to mitigate greenhouse gas emissions to reduce the epidemic potential of dengue in India.
Source: https://www.sciencedirect.com/science/article/pii/S0048969720338584
Ground motion modelling in northwestern Himalaya using stochastic finite-fault method
by Ramees R. Mir & Imtiyaz A. Parvez
Abstract: This study presents estimates of bedrock level peak ground motion at 2346 sites on a regular grid of 0.2° × 0.2° in northwestern (NW) Himalaya from 543 simulated sources, using the stochastic finite-fault, dynamic corner frequency method, with particular emphasis on Kashmir Himalaya. The earthquake catalogue used for simulating synthetic seismograms is compiled by including both pre-instrumental and instrumental era earthquakes of magnitude Mw ≥ 5, dating back to 260 AD. Acceleration time series thus generated are then integrated to obtain velocity and displacement time series, which are all used to construct a suite of hazard maps of the region. Expected PGA values for the Kashmir Himalaya and Muzaffarabad are found to be ~ 0.3–0.5 g and for the epicentral region of the 1905 Kangra event, to be 0.35 g. These values are consistent with other reported results for these areas e.g., Khattri et al. (Tectonophysics 108:93–134, 1984) and Parvez et al. (J Seismol, 2017. https://doi.org/10.1007/s10950-017-9682-0). The PGA values estimated in this study are in general found to be higher than those implied by the official seismic zoning map of India produced by the Bureau of Indian Standards (BIS in Indian Standard criteria for earthquake resistant design of structures part 1 general provisions and buildings (Fifth Revision), vol 1, no 5. Indian Standard, 2002). Even the acceleration-derived intensities for most regions are found to be higher compared with those observed, which apparently is due to the use of a longer duration catalogue (260 AD–2016) for simulation not covered by the observed intensity catalogue and higher magnitude ascribed to historical events. Major events in Kashmir Himalayas, such as those of 1555, 1885 and 2005, are simulated individually to allow comparison with available results. Simulated pseudo-acceleration and velocity response spectra for three sites near the 2005 Kashmir earthquake for which site conditions were available (Okawa in Strong earthquake motion recordings during the Pakistan, 2005/10/8, Earthquake, 2005. https://iisee.kenken.go.jp) are compared with observed spectra. This study provides a first-order ground motion database for safe design of buildings and other infrastructure in the NW Himalayan region.
Source: https://link.springer.com/article/10.1007/s11069-020-04068-8
Characteristics of pre-monsoon convective systems over south peninsular India and neighborhood using tropical rainfall measuring mission's precipitation radar
by Geeta Agnihotri, K. C. Gouda & Someshwar Das
Ten-year climatology of physical properties of convective echoes during pre-monsoon season over south peninsular India and neighborhood are studied using Precipitation Radar dataset onboard Tropical Rainfall Measuring Mission satellite. Attenuation corrected radar reflectivity (Ze) is used to define an intense convective echo (ICE) which is a group of two or more contiguous convective pixels with Ze exceeding 30 dBZ. Height distribution of ICE is right skewed, single modal with mean and median as 7.8 and 7.3 kms. The ICE with area in range of more than 102 to 103 km2 (C) are most frequent (58.5%) followed by smallest scale (D) having area ≤ 102 km2 (37.2%). Large ICE’s (B/C scale) are less frequent (4.2%). Mean areas of ICE’s in D, C and B/C scales are 72.7, 279 and 1932 km2, respectively. The relation between height and area is linear indicating that taller ICE’s are broader. The mean top heights of D, C and B/C scales are 5.5, 8.7 and 14.2 km, respectively. Frequency distributions of the height of 30 and 40 dBZ show single peaks at 5.5 and 4.75 km. Mean heights of 30 dBZ and 40 dBZ are 5.7 and 4.8 km while median heights are 5.5 and 4.7 km. Their cumulative frequency distribution shows that 6 and 3% of ICE cross 10 km height. Reflectivity structures of ICE show that systems over land are intense compared to that over ocean.
Source: https://link.springer.com/article/10.1007/s00703-020-00740-7
Deterministic Seasonal Quantitative Precipitation Forecasts: Benchmark Skill with a GCM
by K. C. Gouda, S. Nahak & P. Goswami
Many applications, from agricultural planning (such as crop choice) to estimation of hydro-power and surface water availability require quantitative precipitation forecasts (QPF). While a large number of studies have addressed the problem of forecasting seasonal Indian summer monsoon (ISM) rainfall over the decades, the emphasis generally has been on simulation and forecasting of rainfall anomalies from long-period mean. However, given the trends in monsoon rainfall, the procedure of considering anomalies has inherent errors; thus reconstruction of actual rainfall from the anomalies does not necessarily provide accurate information. Most QPF have been attempted at short-range forecasts, with a variety of techniques like model output statistics. This work represents evaluation of an atmospheric Variable Resolution General Circulation Model (VRGCM) for QPF during monsoon season. The VRGCM, with variable grid resolution provides relatively high (~ 50 km) resolution over the ISM region, has been validated over all India as well as in different regions like Central and North India, South India, North East India for seasonal forecast of monsoon rainfall. VRGCM simulated QPF appears to provide comparable information as that of anomaly forecasts of monsoon over different regions in India. The forecast skill is appreciable, with significant correlation at all India, South India and North East India regions. The Root Mean Square Error of VRGCM in forecasting quantitative rainfall overall India and Central North India is very low and bit high over South and North East region of India. The performance of VRGCM in forecasting the rainfall in extreme (deficit or excess) monsoon years is also very high with phase synchronisation of 89% in the inter annual variability of rainfall during monsoon at all India scale while the value is about 57%, 76% and 55% over Central North, South and North East India region, respectively.
Source: https://link.springer.com/article/10.1007%2Fs00024-020-02463-7
- Iron limitation study in the North Indian Ocean using model simulations
- Unified Scaling Law for Earthquakes as Applied to Assessment of Seismic Hazard and Associate Risks
- Impact of land-use changes on the genesis and evolution of extreme rainfall event: a case study over Uttarakhand, India
- Future projections of Indian Summer Monsoon under multiple RCPs using a high resolution global climate model multiforcing ensemble simulations
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