Raghavendra Ashrit

• Ph D
• Researcher at National Centre for Medium Range Weather Forecasting

Rivers form a lifeline for the agriculture based economy in India, but recent heavy rainfall events have caused major floods in the rivers resulting in loss of life and property. In order to accurately forecast the stream flow from the rivers firstly, an accurate forecast of rainfall over the river basins (RB) is required. Until recently, for opera...

This work demonstrates the interaction of two different vortices ‘Dana,’ and ‘Trami’ which originated over the Bay of Bengal (BoB) and the South China Sea (SCS) in October 2024, respectively. When two cyclonic storms come near each other, their interaction is called the Fujiwhara Effect (1921). One of the most active cyclogenesis regions is the BoB...

In response to the growing emphasis on transitioning to clean, sustainable energy and the increasing global energy demand, the utilization of renewable resources has notably expanded. Among these resources, wind stands as a significant contributor. Presently, India relies on wind farms for over 25% of its renewable energy production. Considering th...

Accurate predictions of wind power generation several months in advance are crucial for the effective operation and maintenance of wind farms and for facilitating efficient power purchase planning. This study evaluates the performance of the seasonal prediction system of the National Centre for Medium-Range Weather Forecasting in forecasting near-s...

The Mocha cyclone, an extremely severe cyclonic storm (ESCS), moved unusually northeastwardly with a well-organized eyewall structure, underwent rapid intensification (RI), and then entered into coastal areas of Myanmar. It caused heavy rainfall (~90 mm) and gusty winds (~115knots ) over the coastal regions of BIMSTEC countries, such as the coasts...

One of the key attributes of an ensemble prediction system (EPS) is the spread among the members. It plays a crucial role in conveying the uncertainty associated with the forecasted parameters. It is a quantitative measure of forecast uncertainty, provides a range of possible outcomes, and helps in the assessment of risk and decision making. Additi...

Drought, a prolonged natural event, profoundly impacts water resources and societies, particularly in agriculturally dependent nations like India. This study focuses on subseasonal droughts during the Indian summer monsoon season using standardized precipitation index (SPI). Analyzing hindcasts from the National Centre for Medium Range Weather Fore...

Wind Power Forecasting aids grid operators in balancing supply and demand, reduces the reliance on fossil fuel-based backup generation, and helps in the efficient management of energy storage systems. NWP models can provide forecasts ranging from hours to several days ahead, making them invaluable for both operational decision-making and strategic...

This report aims to understand information on the regional climate in India. Indian region is the most important part of South Asia. India's geographical locations are unique, such as the juxtaposition of the Arabian Sea, the Bay of Bengal, and the Indian Ocean. Moreover, the Himalayan ranges spread across Pakistan and India, which function as a wa...

This report aims to understand information on the regional climate in India. Indian region is the most important part of South Asia. India's geographical locations are unique, such as the juxtaposition of the Arabian Sea, the Bay of Bengal, and the Indian Ocean. Moreover, the Himalayan ranges spread across Pakistan and India, which function as a wa...

In the evaluation of heavy rainfall events during JJAS 2023, a consistent threat score is considered. Our findings reveal that, despite a consistent threat score of 0.4, these events exhibit distinct spatial coverage characteristics, encompassing variations in shape, size, and orientation. However, relying on the Total Interest (TI) scores for diff...

This research evaluates lightning events that took place from April to July 2023, resulting in fatalities in Bihar, Uttar Pradesh, Jharkhand, Odisha, and other parts of India. Notably, on 5 th July 2023, 15 lives were lost in Bihar, followed by 7 casualties in Uttar Pradesh. Tragically, on 7th July 2023, Uttar Pradesh witnessed 22 fatalities, inclu...

The advent of weather and climate models has equipped us to forecast or project monsoon rainfall patterns over various spatiotemporal scales; however, utilizing a single model is not usually sufficient to yield accurate projection due to the inherent uncertainties associated with the individual models. An ensemble of models or model runs is often u...

In this study, a super cyclonic storm (Amphan) over Bay of Bengal was analyzed with the National Center for Medium-Range Weather Forecasting, Unified Model (NCUM) and National Center for Environmental Prediction (NCEP) global model data. Further, the weather research and forecasting (WRF) model has been utilized to simulate this super cyclonic stor...

Abstract: The purpose of a Decision Support System (DSS) for nuclear emergencies is to furnish emergency managers with thorough and timely information regarding situations arising from a nuclear accident. The DSS integrates various elements, including the released source term, meteorological conditions, dispersion and deposition in the environment,...

Global surface temperature trends in the last few decades show an increase in extreme heat events, prompting a need for accurate prediction of such events. India's mean temperature has risen by 0.85°C from 1901 to 2015, correlating with a 27% increase in mortality rates and a 24% rise in heatwaves, now the second deadliest natural disaster. A notab...

Multiple record-breaking rainfall events were observed along the Western Ghats (WG) during the recent monsoon seasons (2019–2021). Rainfall amounts of up to > 200 mm/day (Extreme rainfall, ER) were recorded especially over the Mumbai region (19.07 N, 72.8 E) causing flooding, landslides, damage to infrastructure and loss of life. Thus, to enhance t...

India is extremely susceptible to climate change and is anticipated to experience the greatest increase in annual average temperature over the next few decades. There is a tendency for heat waves to be frequent during the summer season (March to June) and sometime in July, mainly in the Northwest, Eastern and Central regions of India. The frequent...

Accurate ensemble forecasts of heavy precipitation in India are vital for many applications and essential for early warning of damaging flood events, especially during the monsoon season. In this study we investigate to what extent Quantile Mapping (QM) and Ensemble Model Output Statistics (EMOS) statistical postprocessing reduce errors in precipit...

Bangladesh has a vibrant culture, diverse landscapes, and resilient people. Bangladesh's climate is diverse and dynamic due to its topography and proximity to the Bay of Bengal. This report uses Climatic Research Unit (CRU) datasets to analyze Bangladesh's rainfall and temperature pattern for seven decades (1951–2020). Studying the rainfall trends...

The Weather Research and Forecasting (WRF) model is an important tool for forecasting weather at regional/local scales in the academic and research communities. The process of WRF model initialization while using the Indian Monsoon Data Assimilation and Analysis (IMDAA) reanalysis dataset as initial and boundary conditions (IC/BC) are addressed in...

Weather extremes can have significant public health impacts. The increasing frequencies of extreme weather events like heavy precipitation, drought, heatwaves, etc, have been associated with climate change in recent years. In recent years, there has been a notable rise in the annual mean temperature across India, with an increase of 0.85 °C observe...

With the advancement of technology, Numerical Weather Prediction (NWP) models have undergone significant upgrades during the last few decades, enabling high-resolutionclimate simulations. ❖ The general circulation models were usually inadequate to address the local and regional aspects due to their low resolution. This problem is better solved by d...

India's rising temperatures and heatwaves have led to increased mortality rates. This research uses Machine Learning (ML) techniques, specifically Support Vector Machine (SVM), Random Forest (RF), Gradient Boost and MLR to improve heatwave predictions across India. The study aims to correct biases in existing Numerical Weather Prediction (NWP) mode...

Heat waves are one of the most dangerous natural hazards in the world. Higher daily peak temperatures as well as duration, intensity and frequency of heat waves are increasing globally due to climate change. In India, the instances of heat waves have increased in recent years along with their intensity which has resulted in the increased number of...

This report documents the performance of the global NCMRWF Unified Model (NCUM-G) analysis and forecast during the winter season (DJF) 2022-23. The verification results are presented to address both forecasters and model developers. The information on biases in the forecasted winds, temperature, humidity, rainfall, etc., is crucial for the forecast...

This comprehensive report assesses the performance of the National Centre for Medium-Range Weather Forecasting (NCMRWF) model forecasts during the 2023 monsoon season (June-September, JJAS). The focus is on real-time medium-range forecasts generated by the Global NCMRWF Unified Model (NCUM-G). The forecast verification is conducted by comparing the...

India has experienced an increase in moist heat - extremes in recent years, which has adversely impacted human health. Extreme weather events such as tropical cyclones and heat waves have the potential to inflict substantial damage on human societies as well as natural ecosystems. A higher intensity of tropical cyclones has been observed during the...

Multiple record-breaking rainfall events were observed along the Western Ghats (WG) during the recent monsoon seasons from 2019-2021. Rainfall amounts of up to >200 mm/day (Extreme rainfall, ER) were recorded especially over the Mumbai region (19.07N, 72.8E) causing flooding, landslides, damage to infrastructure and loss of life. Thus, to enhance t...

Assessment of extreme rainfall events (ERE) is crucial for disaster management. Numerical weather prediction (NWP) model-based predictions often fail to predict the extremes. This could be due to several reasons, including insufficient model resolution to capture the sub-grid scale processes, inadequate high-quality observational data for assimilat...

Characteristics of the atmospheric kinetic energy (KE) spectrum follow a distinct power‐law dependence in the synoptic (k⁻³) and mesoscales (k−5/3), where k is the horizontal wave‐number. The representation of this canonical spectral behaviour provides a testimony of the acceptability of the design, configuration and performance of a numerical weat...

We assess the skill of the fully coupled lagged ensemble forecasts from GloSea5-GC2, for the sub-seasonal to seasonal (S2S) timescale up to 4 weeks, with the aim of understanding how these forecasts might be used in a Ready-Set-Go style decision-making framework. Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG-GPM)...

Northeast Monsoon of South Asia

Rivers form a lifeline for the agriculture based economy in India, but recent heavy rainfall events have caused major floods in the rivers resulting in loss of life and property. In order to accurately forecast the stream flow from the rivers firstly, an accurate forecast of rainfall over the river basins (RB) is required. Until recently, for opera...

Numerical weather prediction (NWP) models are widely used for forecasting heavy rainfall events in the Indian region. However, the accuracy of these models can vary depending on various factors such as model configurations, data assimilation techniques, and physical parameterizations. Traditional verification metrics like the probability of detecti...

For the spatial verification of heatwaves first time we have used the state-of-art technique of object-based (MODE) verification. For the purpose of mitigation and reduction of damages due to heatwaves, timely and accurate forecasts are required. In order to check the accuracy and to generate more confidence in using these forecasts, a thorough ass...

The impact of climate change on emerging economies, including extreme heat events and natural disasters, is a growing public health and economic risk. To effectively respond to these challenges, leveraging new technologies to improve verification and response is crucial. Emerging technologies, such as satellite imagery, remote sensing, and artifici...

Heatwaves are one of the most dangerous natural hazards in the world. Higher daily peak temperatures, duration, intensity and frequency of heatwaves are increasing globally due to climate change. In India, the instances of heatwaves have increased in recent years along with their intensity which has resulted in increased casualties. For the purpose...

Forecasting severe weather events is of immense value since it can help alleviate (if not mitigate) the disastrous impacts to a certain extent. While accurate and precise forecasting is a great challenge, the advances in recent decades in the NWP in India have shown improved accuracy and reliability in the forecasting capabilities, especially for s...

Global numerical weather prediction (NWP) models, including ensemble prediction systems (EPS), are routinely used by the forecasters to predict tropical cyclone (TC) tracks and intensity. However, due to computational restrictions, the EPSs are usually of coarse resolution, which results in poor prediction of TC intensity. The bias in the model pre...

Probabilistic forecasting of tropical cyclone (TC) from ensemble prediction systems provides flow-dependent uncertainty associated with the model forecast and helps in better decision making. NCMRWF global and regional ensemble prediction systems (NEPS-G and NEPS-R) have been used in forecasting the intensity and track of the Super Cyclone ‘Amphan’...

This study aims to evaluate the performance of five global medium-range operational NWP model rainfall forecasts, namely NCUM, UKMO, IMD GFS, NCEP GFS and ECMWF to provide an intercomparison of rainfall forecasts over India in terms of skill in predicting daily rainfall (24-hr accumulated rainfall). Verification and intercomparison of rainfall fore...

Many traditional verification methods are commonly used to assess the performance of numerical weather prediction (NWP) systems in predicting extreme weather like heatwaves using a grid-to-grid approach. These traditional methods figure out only a piece of statistical information’s. While some other state-of-art spatial verification techniques, suc...

This presentation highlights the capability of NCMRWF coupled model in prediction of wind power at Seasonal Scale. The results are based on 23 years of hindcast (1993-2015) and a case study of July 2020 when India witnessed a Wind Power Drought.

Accurate forecasts of visibility are important to avoid disruption in air and highway traffic caused due to the formation of dense fog. However, accurate forecasting of visibility/fog remains a challenge as the genesis and development of fog is a result of many processes. In view of this, models have been developed in recent years to forecast visib...

As a part of the New Generation Verification (NGVer) being developed at the UK Met Office, the Model Evaluation Tools Plus (METplus) package is now being used for seamless verification of operational forecasts (global and regional) at the National Centre for Medium-Range Weather Forecasting (NCMRWF). MET version 10.0 along with METPLUS 4.0.0 is ins...

As a part of the New Generation Verification (NGVer) being developed at the UK Met Office the Model Evaluation Tools Plus (METplus) package is now being used for seamless verification of operational ensemble forecasts (global and regional) at the National Centre for Medium Range Weather Forecasting (NCMRWF). MET version 10.0 along with METPLUS 4.0....

As a part of the New Generation Verification (NGVer) being developed at the UK Met Office, the Model Evaluation Tools Plus (METplus) package is now being used for seamless verification of operational forecasts (global and regional) at the National Centre for Medium-Range Weather Forecasting (NCMRWF). MET version 10.0 along with METPLUS 4.0.0 is ins...

Operational forecasting of tropical cyclone (TC) track and intensity in the India Meteorological Department (IMD) relies more and more on the numerical weather prediction (NWP) model guidance from national and international agencies particularly, on the medium range (24–120 h). Any improvement in TC forecasts by the NWP models enhances the operatio...

Increased resolution of Numerical Weather Prediction (NWP) models can lead to improved prediction of heavy rains; however, the forecasts often suffer from location mismatch and intensity errors which can lead to poor traditional verification scores. Spatial verification can provide more realistic statistics to ascertain the quality of forecasts. Th...

This study focuses on assessing different quantile mapping (QM) bias correction approaches based on empirical and parametric methods to bias-correct the Indian Monsoon Data Assimilation and Analysis (IMDAA) precipitation data subsequently calibrate the National Centre for Medium Range Weather Forecasting (NCMRWF) Unified Model operational forecasts...

Reanalysis datasets play a vital role in different stages of renewable resource assessment though it has certain limitations. In recent years, different regional reanalysis datasets are being developed for better representation of meteorological parameters. The present study introduces the suitability of the application of a high-resolution Indian...

Forecasting of heavy rainfall events is still a challenge even for the most advanced state-of-art high resolution NWP modelling systems. Very often the models fail to accurately predict the track and movement of the low pressure systems leading to large spatial errors in the predicted rain. Quantification of errors in forecast rainfall location and...

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Dust storms are common over north-west parts of India during the pre-monsoon season. The main objective of this study is to assess the movement of dust over Indian region during a dust event using the dust aerosol optical depth (AOD) forecast from an operational numerical weather prediction model. Observed values of visibility, wind speed are used...

Countries adjoining the North Indian Ocean (NIO) region are among the world's worst affected areas by tropical cyclones (TCs). An increase in frequency and intensity of TCs affecting this basin is noticed in recent years. Timely and accurate prediction of a TC can lead to a decrease in damages to life and property caused by the cyclone. In recent t...

The ensemble predictions were more skillful than the deterministic forecasts , as they were able to predict rainfall anomalies.

Performance of four mesoscale models namely, the MM5, ETA, RSM and WRF, run at NCMRWF for short range weather forecasting has been examined during monsoon-2006. Evaluation is carried out based upon comparisons between observations and day-1 and day-3 forecasts of wind, temperature , specific humidity, geopotential height, rainfall, systematic error...

During August 2018 and 2019 the southern state of India, Kerala received unprecedented heavy rainfall which led to widespread flooding. We aim to characterize the convective nature of these events and the large-scale atmospheric forcing, while exploring their predictability by three state of the art global prediction systems, the National Centre fo...

Prediction of heavy/extreme rains is still a challenge, even for the most advanced state-of-the-art high-resolution Numerical Weather Prediction (NWP) modelling systems. Hydrological models use the rainfall forecasts from the NWP models as input. This study evaluates the performance of the UK Met Office Unified Model (UM) in predicting the rainfall...

Winter report using NCUM model

Verification of forecasts and warnings of high-impact weather is needed by the meteorological centres, but how to perform it still presents many open questions, starting from which data are suitable as reference. This paper reviews new observations which can be considered for the verification of high-impact weather and provides advice for their usa...

NCMRWF global ensemble prediction system (NEPS-G) is being used for operational forecasting of tropical cyclones (TC) since the year 2016. The NEPS-G was upgraded and its horizontal resolution was increased from 33 km to 12 km in the year 2018. The upgraded NEPS-G has shown improved performance in forecasting tropical cyclones over the North Indian...

There are various methods available for the verification of cyclones. The Object-based diagnostic evaluation is one of the techniques. This is an object-based technique of spatial verification methods that provides information that is not possible to obtain using general traditional grid-point based verification methods. It objectively identifies s...

This paper deals with the analysis of the ability of the operational global ensemble prediction system (EPS) at the National Centre for Medium Range Weather Forecasting (NCMRWF, NEPS in predicting the probabilities of the maximum 2 m temperature (TMAX). The mean of the TMAX forecasts from NEPS are bias corrected (1st moment) using the technique of...

The Object-based diagnostic evaluation is one of the advanced verification techniques. This is an object-based technique of spatial verification methods which provides information which is not possible to obtain using general traditional grid-point based verification methods. It objectively identifies simple objects in rainfall fields at different...

In recent times, instances of intense heat waves have increased over the Indian subcontinent. This increase in temperature has an adverse effect on human health and the economy. Over India, such high temperatures are usually seen during the months of March–May (summer). For weather forecasters, it is a challenging job to accurately predict the timi...

Verification of high-impact weather is needed by the Meteorological Centres, but how to perform it still presents many open questions, starting from which data are suitable as reference. This paper reviews new observations which can be considered for the verification of high-impact weather, and provides advice for their usage in objective verificat...

This report provides a compilation rainfall forecast verification for the MoES models during monsoon season (JJAS) 2019. The verification results are focused on the rainfall forecasts since the India Meteorological Department (IMD) is using the NWP model precipitation forecast for day to day operational weather forecast in short to medium range. Th...

This report provides a compilation of the NWP model forecast verification for the MoES models during monsoon season (JJAS) 2019. The verification results are focused on upper air fields from the two high resolution deterministic models namely (i) IMD’s GFS and (ii) NCMRWF’s NCUM generating real time NWP forecasts in the medium range time scale (up...

The monsoon Depressions form significant rainfall activity and havoc, at times, along their track particularly over eastern India. NWP models still have challenge in accurate prediction of track and intensity of the Depressions. This often leads to inaccurate forecast in rainfall intensity, area and distribution. This report summarizes the results...

This report provides a compilation of the NWP model forecast verification for the MoES models during monsoon season (JJAS) 2019. The verification results are focused on upper air fields from the two high resolution deterministic models namely (i) IMD’s GFS and (ii) NCMRWF’s NCUM generating real time NWP forecasts in the medium range time scale (up...

This report provides a compilation rainfall forecast verification for the MoES models during monsoon season (JJAS) 2019. The verification results are focused on the rainfall forecasts since the India Meteorological Department (IMD) is using the NWP model precipitation forecast for day to day operational weather forecast in short to medium range. Th...

This report gives a detailed summary of the verification of the NCMRWF model forecasts during the recent Super Cyclone (SUCS) ‘Amphan’ during (16-21 May2020). The mean (all models) initial position error is 48 km with highest error of 53 km in NCUM-R. The mean (all models) 24-hr track error is around 54 km with highest error of 78 km in NCUM-R. Sim...

This report provides a compilation of the verification for the MoES operational NWP model forecast during monsoon season (JJAS) 2019. The verification and intercomparison results are presented for few large scale upper air fields from the two high resolution deterministic models namely (i) GFS and (ii) NCUM and ensemble models namely (iii) GEFS and...

This paper deals with the comparison of cyclone forecasts from the two versions of the operational global ensemble prediction system (EPS) at the National Centre for Medium Range Weather Forecasting (NEPS). The previous version had a horizontal resolution of 33 km with 44 ensemble members (NEPS) whereas the updated version of this EPS has a resolut...

The southern Indian state of Kerala experienced exceptionally high rainfallduring August 2018, which led to devastating floods in many parts of the state.Prediction and early warning of severe weather events in vulnerable areas iscrucial for disaster management agencies in order to protect life and property.In recent years, state-of-the-art numeric...

The southern Indian state of Kerala experienced exceptionally high rainfall during August 2018, which led to devastating floods in many parts of the state. Prediction and early warning of severe weather events in vulnerable areas is crucial for disaster management agencies in order to protect life and property. In recent years, state‐of‐the‐art num...

An international conference on “Ensemble Methods in Modelling and Data Assimilation (EMMDA)” was organised by NCMRWF during 24-26 February 2020. The international conference was inaugurated by the Chief Guest Dr. M. Mohapatra, Director General of Meteorology, IMD & Permanent Representative to WMO on 24th February in the presence of Dr. Vipin Chandr...

The Indian Monsoon Data Assimilation and Analysis (IMDAA) is a regional high‐resolution atmospheric reanalysis over the Indian subcontinent. This regional reanalysis over India is the first of its kind and is produced by the National Centre for Medium Range Weather Forecasting and Met Office, UK, in collaboration with the India Meteorological Depar...

सार: मॉडल भौतिकी और रिजोलूशन में प्रमुख सुधार सहित एन.डब्लू.पी. मॉडल में कई महत्वपूर्ण सुधार के बावजूद, इन मॉडलों में अभी भी सिस्टेमेटिक बायस (व्यवस्थित अभिनति) से ग्रसित हैं। एक मॉडल से इन सिस्टेमेटिक बायसों को दूर करने के लिए कई तरीके उपलब्ध हैं, उदाहरण के लिए सांख्यिकीय प्रोसेसिंग विधि को लागू करके। वर्तमान अध्ययन में हमने डिकेयिगिं एवरेज बायस क...

इस अध्ययन में उपग्रह से प्राप्त आंकडे तथा पुनर्विश्लेषण आंकडों का उपयोग करके मध्य और उत्तर भारती क्षेत्र में हुई भारी वर्षा के प्रकरण की नैदानिक जांच किया है । 1 जनवरी 2012 को संगठित उष्णकटिबंधीय और बहिउष्णकटिबंधीय बल ने तीव्र वर्षा को प्रेरित किया, यह घटना इस मायने में अद्वितीय है। समीपवर्ती उष्णकटिबंधीय महासागर से आने वाली नमी विंडसैट (मल्टी-फ़...

This study, first of its kind evaluates the suitability of Indian Monsoon Data Assimilation and Analysis (IMDAA) reanalysis data products for offshore wind resource assessment. IMDAA is a high resolution (12km) reanalysis data over Indian region spanning 1979-2018. Near surface (at 50m) wind speed and direction from IMDAA have been validated agains...

The Indian Monsoon Data Assimilation and Analysis (IMDAA) is a regional high‐resolution atmospheric reanalysis over the Indian subcontinent. This regional reanalysis over India is the first of its kind and is produced by the National Centre for Medium Range Weather Forecasting and Met Office, UK, in collaboration with the India Meteorological Depar...

In spite of many significant improvements in NWP models including major improvements in the model physics and resolution, these models still suffer from systematic biases. There are several methods available to remove these systematic errors from a model, for example by applying statistical post processing algorithms. In the current study we have m...

In spite of many significant improvements in NWP models including major improvements in the model physics and resolution, these models still suffer from systematic biases. There are several methods available to remove these systematic errors from a model, for example by applying statistical post processing algorithms. In the current study we have m...

This presentation highlights two major research findings (wind power perspective): - 1. How the wind speed has decreased in the last four decades over different wind rich states in India using MERRA data? 2. What is the future trend of wind speed using one of the CMIP5 climate models data?

Prediction of heavy rains associated with orography is still a challenge, even for the most advanced state-of-art high-resolution Numerical Weather Prediction (NWP) modeling systems. The aim of this study is to evaluate the performance of UK Met Office Unified Model (UM) in predicting heavy and very heavy rainfall exceeding 80th and 90th percentile...