Articles written in Journal of Earth System Science

    • Spatio-temporal variability of summer monsoon rainfall over Orissa in relation to low pressure systems

      M Mohapatra U C Mohanty

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      The summer monsoon rainfall over Orissa occurs mostly due to low pressure systems (LPS) developing over the Bay of Bengal and moving along the monsoon trough. A study is hence undertaken to find out characteristic features of the relationship between LPS over different regions and rain-fall over Orissa during the summer monsoon season (June-September). For this purpose, rainfall and rainy days over 31 selected stations in Orissa and LPS days over Orissa and adjoining land and sea regions during different monsoon months and the season as a whole over a period of 20 years (1980-1999) are analysed. The principal objective of this study is to find out the role of LPS on spatial and temporal variability of summer monsoon rainfall over Orissa.

      The rainfall has been significantly less than normal over most parts of Orissa except the eastern side of Eastern Ghats during July and hence during the season as a whole due to a significantly less number of LPS days over northwest Bay in July over the period of 1980-1999. The seasonal rainfall shows higher interannual variation (increase in coefficient of variation by about 5%) during 1980-1999 than that during 1901-1990 over most parts of Orissa except northeast Orissa. Most parts of Orissa, especially the region extending from central part of coastal Orissa to western Orissa (central zone) and western side of the Eastern Ghats get more seasonal monsoon rainfall with the development and persistence of LPS over northwest Bay and their subsequent movement and persistence over Orissa. The north Orissa adjoining central zone also gets more seasonal rainfall with development and persistence of LPS over northwest Bay. While the seasonal rainfall over the western side of the Eastern Ghats is adversely affected due to increase in LPS days over west central Bay, Jharkhand and Bangladesh, that over the eastern side of the Eastern Ghats is adversely affected due to increase in LPS days over all the regions to the north of Orissa. There are significant decreasing trends in rainfall and number of rainy days over some parts of southwest Orissa during June and decreasing trends in rainy days over some parts of north interior Orissa and central part of coastal Orissa during July over the period of 1980-1999

    • Seasonal forecasting of tropical cyclogenesis over the North Indian Ocean

      D R Pattanaik M Mohapatra

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      Over the North Indian Ocean (NIO) and particularly over the Bay of Bengal (BoB), the post-monsoon season from October to December (OND) are known to produce tropical cyclones, which cause damage to life and property over India and many neighbouring countries. The variability of frequency of cyclonicdisturbances (CDs) during OND season is found to be associated with variability of previous large-scale features during monsoon season from June to September, which is used to develop seasonal forecast model of CDs frequency over the BoB and NIO based on principal component regression (PCR). Sixdynamical/thermodynamical parameters during previous June–August, viz., (i) sea surface temperature (SST) over the equatorial central Pacific, (ii) sea level pressure (SLP) over the southeastern equatorial Indian Ocean, (iii) meridional wind over the eastern equatorial Indian Ocean at 850 hPa, (iv) strength ofupper level easterly, (v) strength of monsoon westerly over North Indian Ocean at 850 hPa, and (vi) SST over the northwest Pacific having significant and stable relationship with CDs over BoB in subsequent OND season are used in PCR model for a training period of 40 years (1971–2010) and the latest four years (2011–2014) are used for validation. The PCR model indicates highly significant correlation coefficient of 0.77 (0.76) between forecast and observed frequency of CD over the BoB (NIO) for the whole period of 44 years and is associated with the root mean square error and mean absolute error ≤ 1 CD. With respect to the category forecast of CD frequency over BoB and NIO, the Hit score is found to be about 63% and the Relative Operating Curves (ROC) for above and below normal forecast is found to be having much better forecast skill than the climatology. The PCR model performs very well, particularly for the above and below normal CD year over the BoB and the NIO, during the test period from 2011 to 2014.

    • Validation of a satellite-based cyclogenesis technique over the North Indian Ocean

      Suman Goyal M Mohapatra Ashish Kumar S K Dube Kushagra Rajendra P Goswami

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      Indian region is severely affected by the tropical cyclones (TCs) due to the long coast line of about 7500 km. Hence, whenever any low level circulation (LLC) forms over the Indian Seas, the prediction of its intensification into a TC is very essential for the management of TC disaster. Satellite Application Centre (SAC) of Indian Space Research Organization (ISRO), Ahmedabad, has developed a techniqueto predict TCs based on scatterometer-derived winds from the polar orbiting satellite, QuikSCAT and Oceansat-II. The India Meteorological Department (IMD) has acquired the technique and verified it for the years 2010–2013 for operational use. The model is based on the concept of analogs of the sea surfacewind distribution at the stage of LLC or vortex (T1.0) as per Dvorak’s classifications, which eventually leads to cyclogenesis (T2.5). The results indicate that the developed model could predict cyclogenesis with a probability of detection of 61% and critical success index of 0.29. However, it shows high overpredictionof the model is better over the Bay of Bengal than over Arabian Sea and during post-monsoon season (September–December) than in pre-monsoon season (March–June).

    • Meteorological features associated with unprecedented precipitation over India during 1st week of March 2015

      Naresh Kumar M Mohapatra A K Jaswal

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      Unprecedented precipitation along with heavy falls occurred over many parts of India from 28th February to 2nd March 2015. Many of the stations of northwest and central India received an all time high 24 hr cumulative precipitation of March during this period. Even the national capital, New Delhi, broke all the previous historical 24 hr rainfall records of the last 100 years to the rainfall record in March 2015. Due to this event, huge loss to agricultural and horticultural crops occurred in several parts of India. In the present study, an attempt is made to understand the various meteorological features associated with this unprecedented precipitation event over India. It occurred due to the presence of an intense western disturbance (WD) over Afghanistan and neighbouring areas in the form of north–south oriented deep trough in westerlies in middle and upper tropospheric levels with its southern end deep in the Arabian Sea, which pumped huge moisture feed over Indian region. Also, there was a jet stream with core wind speed up to 160 knots that generated high positive divergence at upper tropospheric level over Indian region; along with this there was high magnitude of negative vertical velocity and velocity convergence were there at middle tropospheric level. It caused intense upward motion and forced lower levels air to rise and strengthen the lower levels cyclonic circulations (CCs)/Lows. Moreover, the induced CCs/Lows at lower tropospheric levels associated with WD were more towards south of its normal position. Additionally, there was wind confluence over central parts of India due to westerlies in association with WD and easterlies from anticyclone over north Bay of Bengal. Thus, intense WD along with wind confluence between westerlies and easterlies caused unprecedented precipitation over India during the 1st week of March 2015.

    • Satellite-based technique for nowcasting of thunderstorms over Indian region

      Suman Goyal Ashish Kumar M Mohapatra L S Rathore S K Dube Rahul Saxena R K Giri

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      India experiences severe thunderstorms during the months, March–June. But these systems are not predicted well, mainly due to the absence of mesoscale observational network over Indian region and the expert system. As these are short lived systems, the nowcast is attempted worldwide based on satellite and radar observations. Due to inadequate radar network, satellite plays the dominant role for nowcast of these thunderstorms. In this study, a nowcast based algorithm ForTracc developed by Vila et al. (Weather Forecast 23:233–245, 2008) has been examined over the Indian region using Infrared Channel (10.8 μm) of INSAT-3D for prediction of Mesoscale Convective Systems (MCS). In this technique, the current location and intensity in terms of Cloud Top Brightness Temperature (CTBT) of the MCS are extrapolated. The purpose of this study is to validate this satellite-based nowcasting technique for Convective Cloud Clusters that helps in optimum utilization of satellite data and improve the nowcasting. The model could predict reasonably the minimum CTBT of the convective cell with average absolute error (AAE) of <7 K for different lead periods (30–180 min). However, it was underestimated for all the lead periods of forecasts. The AAE in the forecasts of size of the cluster varies from about 3×104 km2 for 30-min forecast to 7×104 km2 for 120-min forecast. The mean absolute error in prediction of size is above 31–38% of actual size for different lead periods of forecasts from 30 to 180 min. There is over estimation in prediction of size for 30 and 60 min forecasts (17% and 2.6% of actual size of the cluster, respectively) and underestimation in 90 to 180-min forecasts (–2.4% to –28%). The direct position error (DPE) based on the location of minimum CTBT ranges from 70 to 144 km for 30–180-min forecast respectively.

    • Robustness of best track data and associated cyclone activity over the North Indian Ocean region during and prior to satellite era


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      There are few studies focusing on analysing climatological variation in cyclone activity by utilising the best track data provided by the India Meteorological Department (IMD) over the North Indian Ocean (NIO). The result of such studies has been beneficial in decision-making by government and meteorological agencies. It is essential to assess the quality and reliability of the currently available version of the dataset so that its robustness can be established and the current study focuses on this aspect. The analysis indicates that there is an improvement over the years in the quality and availability of the data related to cyclones over NIO, especially in terms of frequency of genesis, intensity, landfall etc. The available data from 1961 onwards has been found robust enough with the advent of satellite technology. However, there can be still missing information and inaccuracy in determining the location and intensity of cyclones during the polar satellite era (1961–1973). The study also indicates undercount of severe cyclones during the pre-satellite era. Considering the relatively smaller size of NIO basin, these errors can be neglected and thus, the IMD best track data can be considered as reliable enough for analysing cyclone activity in this region.

    • Performance of numerical weather prediction models in predicting track of recurving cyclone Vayu over Arabian Sea during June 2019


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      A tropical cyclone (TC) Vayu developed over the Arabian Sea during June, 2019. It followed a northward track from southeast Arabian Sea to northeast Arabian Sea close to Gujarat coast during 10–12 June 2019 as a very severe cyclonic storm. It skirted south Gujarat coast by recurving west-northwestwards during 13th–14th June and again made a northeastward recurvature on 16th June towards Gujarat coast. However, it weakened over Sea on 17th. There was large divergence among various models in predicting the track of TC Vayu leading to over warning for Gujarat state and also delay in dewarning leading to evacuation of people from coastal region. Hence, a study has thus been taken up to analyze the performance of various numerical weather prediction (NWP) models in forecasting the track of TC Vayu so as to find out the reason for above limitation of NWP models. Results suggest that there is a need to relook into the existing multi-model ensemble (MME) technique which outperforms individual models in track forecasting. There is also a need to improve the individual deterministic model guidance so as to suitably represent the interaction between mid-latitude westerlies with the TC and steering anticyclone by improving the initial and boundary conditions through augmented direct and remotely sensed observations over the Arabian Sea and their assimilation in NWP models.


      $\bullet$ The multiple interactions among the wind fields of TC Vayu, middle latitude westerlies and anticyclones over central India & Arabian Peninsula led to the unique track of Vayu with two recurvatures in its life cycle.

      $\bullet$ The prediction of time and point of recurvature in the track of TCs is still a challenge for the NWP models and hence the operational forecast, as models could not represent the interaction of mid-latitude westerlies with the TC and steering anticyclone over either side of the TC.

      $\bullet$ Comparing the average track forecast errors of different models and multi-model ensemble (MME) for the recurving TCs during 2009–2019, the MME shows minimum average track forecast error. However, the consistency in MME based track forecast decreases with increase in lead period.

      $\bullet$ There is a need to look into the existing MME and improve it by re-defining the best constituent members and improving the performance of individual models through augmentation of direct & remotely sensed observations, data assimilation and the physical processes in the model.

    • Evaluation of heavy rainfall warnings of India National Weather Forecasting Service for monsoon season (2002–2018)


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      The major objective of any national weather forecasting services is to provide weather forecast and warnings and other meteorological related information to the public and government for the safety of life and property and economic activities. The heavy rainfall causes huge loss to the public in form of flood and landslide in varying severity mainly during monsoon season (June–September). Hence its accurate prediction is essential and the accuracy of prediction needs to be verified quantitatively to evaluate its strength and weakness. The National Weather Forecasting Centre (NWFC) of India Meteorological Department (IMD) issues heavy rainfall (HR) warnings for the safety of life and property of the public. In this study, verification of operational heavy rainfall (HR) warning issued by NWFC of IMD for 36 sub-divisions of India is carried out. The verification scores presented in the study are for 24 hrs (D1), 48 hrs (D2) and 72 hrs (D3) lead period average warning skills during 2014–2018 and year-wise trend of the HR warnings for the period 2002–2018. In general, it is observed that there are significant improvements in skill scores in recent years. The improvement in D3 is at higher rate as compared to D1 scores. The improvement in the recent years is mainly due to improvement in model resolution and data assimilation in the Numerical Prediction (NWP) Models runs by Ministry of Earth Sciences (MoES), Government of India and their interpretation and utilization by the forecasters for objective consensus forecast using an objective decision support system and synoptic value addition.


      $\bullet$ There is significant improvement in heavy rainfall warning skill of India Meteorological Department during monsoon season in recent two years (2017 and 2018) as compared to 2002–2016.

      $\bullet$ The skill scores namely, Probability of Detection (PoD), Critical Success Index (CSI) and Heidke Skill Score (HSI) has improved by 48%, 46% and 33%, respectively, as compared to mean of scores between 2002–2016 for Day 1 (D1) warning.

      $\bullet$ In Day 3 (D3) warning, there is an improvement by 69%, 54% and 54% in PoD, CSI and HSS respectively during 2017–2018 as compared to mean of 2013–2015. The improvement in D3 warning is at higher rate as compared to D1 warning.

      $\bullet$ In general, the skill scores are higher over the regions with higher frequency of heavy rainfall and lower over less prone regions of heavy rainfall.

      $\bullet$ These improvements in the forecast warning skill may be attributed to availability and use of latest forecasting models with high resolution and better data assimilation. Apart from the above, the structured monitoring of the monsoon circulations parameters, interpretation of NWP models guidance through Forecast Demonstration Project (FDP), objective consensus through decision support system and subjective consensus amongst the forecasters through video conference contributed significantly improved HR warning in recent years.

    • Spatial and temporal variation in daily precipitation indices over Western Himalayas


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      In the recent past, there were extensive floods in the Western Himalayan region (WHR) due to continuous long spells of heavy rainfall for 3–4 days that caused a huge loss in life and property over the region. WHR is a data sparse region, with limited meteorological stations having a continuous long spell of daily precipitation data. In the present study, spatial and temporal variability of seasonal as well as annual precipitation, precipitation days and maximum accumulated daily, 2 days, 3 days, 4 days and 5 days precipitation over WHR is considered by using daily precipitation data of 18 meteorological stations of the region. Out of 18 meteorological stations, five stations have continuous data from 1901 to 1980 and remaining 13 stations data is considered for their common period from 1981 to 2014. Accordingly, the analysis is carried out in two parts, first for 1901–1980 (for 5 stations) and second for 1981–2014 (for all the 18 stations). The analysis suggests high variability in the spatial and temporal distribution of seasonal as well as maximum accumulated daily to 5 days precipitation over WHR. In general, increasing trends in maximum accumulated precipitation in lower altitude stations and decreasing trends in higher altitude stations are observed in monsoon season and vice-versa in the winter season during the period 1981–2014. The increase in maximum accumulated daily to 5 days precipitation is up to 9.7 mm per decade during 1901–1980 and is up to 45.5 mm per decade during 1981–2014 in monsoon season in lower altitude stations. Thus, the increase in maximum accumulated precipitation during monsoon season becomes manifold during 1981–2014 as compared to the period 1901–1980.

    • Comparative analysis of vital parameters of extremely severe cyclonic storms Phailin and Hudhud over the Bay of Bengal


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      Two extremely severe cyclonic storms (ESCSs) Phailin and Hudhud developed over the Bay of Bengal (BoB) during October 2013 and 2014 and crossed the east coast of India near Gopalpur (Odisha) and Visakhapatnam (Andhra Pradesh) at 1700 UTC of 12th October 2013 and 0700 UTC of 12th October 2014, respectively, causing immense loss of property. Considering the devastating effect associated with the typical characteristics of the two tropical cyclones (TCs) and their occurrence during same period of the post-monsoon season, a study has been undertaken to compare the vital parameters including location, movement, intensity, size, etc., of these TCs. The results of this study can be utilized for better understanding and prediction of structural characteristics of TCs over the north Indian Ocean (NIO) and hence the associated adverse weather like heavy rain, gale wind and storm surge. The higher intensity,higher rate of intensification, longer duration in very severe cyclonic storm (VSCS) or higher stage, lower rate of decay after landfall and larger size were the typical characteristics in the case of TC Phailin leading to its higher damage potential in terms of accumulated cyclone energy (ACE) and hence higher loss interms of power dissipation index (PDI) as compared to TC Hudhud.


      $\bullet$ The damage potential and losses were higher in case of tropical cyclone (TC) Phailin due to higher intensity, rapid intensification, longer duration in very severe cyclonic storm (VSCS)/extremely severe cyclonic storm (ESCS) stage, lower rate of decay after landfall and larger size as compared to TC Hudhud.

      $\bullet$ The introduction of Doppler Weather Radars in recent years and improved modelling capabilities blended with subjective value addition through synoptic guidance enabled IMD to accurately monitor the track, intensity and landfall characteristics of these TCs.

      $\bullet$ Though, the track forecast difficulty was higher in case of Hudhud as compared to Phailin, the errors were less in Hudhud and its forecast was more skillful due to improvements in numerical weather prediction (NWP) modelling in 2014. However, the intensity forecast difficulty was higher in case of Phailin as compared to Hudhud due to rapid intensification which could not be predicted by the dynamical and statistical models of India Meteorological Department (IMD).

      $\bullet$ There is scope to improve NWP models and hence the operational intensity forecast especially rapid intensification forecasting.

    • Ocean state forecasting during VSCS Ockhi and a note on what we learned from its characteristics: A forecasting perspective


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      Tropical Cyclone Ockhi was an intense cyclone, with a peculiar and long track, in the Arabian Sea in 2017. It caused severe damage to coastal infrastructure and death of 282 people. Indian National Centre for Ocean Information Services (INCOIS) issued the Joint INCOIS-IMD (India Meteorological Department) bulletins on the Ocean State Forecasts (OSF) and alerts/warnings during Ockhi. Validation of the OSF from INCOIS using buoys reveals that the forecasts were in good agreement with the observations [average correlation 0.9, RMSE ${\le}$0.8 m (for larger waves), and scatter index ${\le}$25%]. Climatological analysis of Genesis Potential Index (GPI) suggests that the southeast Arabian Sea, where the TC-Ockhi was intensified, had all the favourable conditions for intensification during November/December. Moreover, it was found that four days before the genesis of Ockhi, the environmental vorticity and relative humidity were more favourable for the cyclogenesis compared to vertical wind shear and potential intensity. The intensification rate was rapid as experienced by earlier cyclones in this region. Also, the cyclone track closely matched the background tropospheric winds. The present study suggests that the forecasters should look into the background dynamic and thermodynamic conditions extensively in addition to multi-model guidance to better predict the genesis, intensity and track of the cyclones.


      $\bullet$ In the Arabian Sea, during the TC-Ockhi, the forecasts of wave parameters from the model forced with bias-corrected ECMWF winds resulted in very good agreement with observations.

      $\bullet$ Climatologically, TC-Ockhi region has large potential for the genesis and intensification of TC due to an enhanced low-level cyclonic vorticity and the reduction in vertical wind shear.

      $\bullet$ During the TC-Ockhi period, low-level vorticity and mid-tropospheric relative humidity were the dominant contributing factors, which lead to an enhanced GPI in the Arabian Sea.

      $\bullet$ TC-Ockhi also had rapid intensification in a similar fashion the earlier cyclones in this region behaved.

      $\bullet$ There is no abnormality also in the TC-Ockhi track, as the TC-Ockhi track matches well with the background tropospheric flow.

    • An overview of the Satellite Consensus (SATCON) algorithm to estimate tropical cyclone intensity over the North Indian Ocean


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      Consensus-based algorithm for estimating the current intensity (CI) of tropical cyclones (TCs) combining infrared and microwave-based intensity estimates is used by the Cooperative Institute for Meteorological Satellite Studies (CIMSS) to generate a satellite-based consensus (SATCON) on TC intensity. In the present study, an attempt has been made to evaluate the performance of the SATCON method for estimation of TC intensity over the North Indian Ocean during 2016–2020 (5 years). For this purpose, the SATCON based algorithm has been evaluated for 22 TCs over the NIO, including 12 TCs over the Bay of Bengal (BOB) and 10 TCs over the Arabian Sea (AS), and the estimates have been compared with besttrack estimates of the Regional Specialized Meteorological Centre (RSMC), New Delhi. Both the maximum sustained surface winds (V$_{max}$) and estimated central pressure (ECP) have been compared for the different ‘T’ numbers and different categories of the storm during the year as a whole and during the premonsoon (March–May) and post-monsoon (October–December) seasons. The SATCON algorithm performance is found to be reasonably good in estimating the intensity of stronger TCs (T ${\ge}$ 4.0). It overestimates the intensity of weaker TCs (T ${\le}$ 3.5) and also for very strong TCs (T6.0 or more). Its performance is found to be better in the post-monsoon season over the BOB and the AS.

    • Evaluation of the Global Ensemble Forecast System (GEFS T1534) for the probabilistic prediction of cyclonic disturbances over the North Indian Ocean during 2020 and 2021


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      With increasing number of cyclonic disturbances (CDs) over the North Indian Ocean, the prediction of pre-genesis, along with the accurate forecast of the track and intensity, is the need of the hour. The present study evaluates the skill of prediction of genesis as well as the veriBcation of CDs (total of 16 cases are considered) that occurred during the year 2020–2021, using Global Ensemble Forecast System (GEFS) T1534. Different initial conditions with longer lead hours are analysed for genesis, track, intensity and landfall errors. The model has the ability to predict genesis location with error of about ${\sim}$200 km at day 2 lead. VeriBcation of all CDs indicates that the landfall in terms of time and position is well predicted by the model. In general, the model shows the northward bias in genesis location error for the initial 12 hours and after that southwestward bias. From depression till dissipation, the track error for ensemble mean is less than that of the control run. The track error is less than 150 km for ensemble mean till day 3 and is about 220 km on day 4. The model shows northward bias in predicting the track of CDs. For predicting the landfall locations, southwestward bias is shown by model. The probabilistic ensemble skill scores are also evaluated for GEFS T1534, which shows reasonable skill.

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