Evaluation of High-Resolution WRF Model Simulations of Surface Wind over the West Coast of India

Vishnu,; Francis, Susan T.

doi:10.1080/16742834.2014.11447207

Cited by 11 publications

(3 citation statements)

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“…Further, the wind speeds estimated by WRF are compared with that observed by four different moored buoys, as shown in figure 4. As the moored buoy observations are at 3 m, the wind speeds are extrapolated to 10 m height [55], to compare with WRF results. It is interesting to note that WRF can capture the peak intensity wind speeds when the cyclone Ockhi crosses the buoy locations.…”

Section: Comparisons With Buoy Observationsmentioning

confidence: 99%

On the understanding of very severe cyclone storm Ockhi with the WRF-ARW model

Mukherjee

Balaji

2022

Environ. Res.: Climate

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Understanding the dynamics of tropical cyclones (TC) in terms of intensity, and their trajectory is essential for adequate early warning and mitigation. The present study attempts to understand the synoptic features of the recent TC Ockhi through a simulation-based approach with the Weather Research and Forecasting (WRF, version 3.8.1) model. Ockhi is considered as a unique TC that originated from depression in the Bay of Bengal on 29 Nov 2017, recurved towards the Arabian Sea, where it intensified into a very severe cyclone storm and weakened on 5 Dec 2017. WRF model forced with initial condition from (Global Forecasting System) GFS data and Sea Surface Temperature (SST) from Group for High-Resolution SST (GHRSST) product for different lead times to test the potential sensitivity of the model. One with an extended period from 20 Nov to 20 Dec. 2017 and another initiated from 27 Nov to 6 Dec 2017. Comparison of the simulated track with the best track estimates from the Indian Meteorological Department (IMD) indicated an overall track deviation greater than 100Km for both the simulations. The analysis with the extended lead time simulation indicates that the WRF simulated sea level pressure (SLP) and wind intensity are close to that observed by Arabian sea buoys; CB02, AD08, AD10, and AD07. Daily averaged wind estimate comparison of WRF1 with Scatsat-1 and ERA-5 indicates that the model is slightly overestimating, whereas comparison of peak wind intensity with the time instantaneous swath product of Scatsat-1 leads to underestimation. Analysis of various simulated synoptic features of the cyclone, as discussed in this paper, indicates that the model is skillful in capturing the various stages of cyclone Ockhi.

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Section: Comparisons With Buoy Observationsmentioning

confidence: 99%

On the understanding of very severe cyclone storm Ockhi with the WRF-ARW model

Mukherjee

Balaji

2022

Environ. Res.: Climate

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“…These variations include transitions from open water to land along complex coastlines and around lakes, and variations in land cover and land use. Thus, regional models can simulate land-sea breezes and lake breezes with a high degree of realism, along with the localized suppression of the land-water temperature gradient in the coastal zone that results (Hughes et al 2007;Vishnu and Francis 2014). Regional models also provide much more realistic distributions of "lake effect" precipitation through resolution of local coastlines and topography than is possible with global models (e.g., Wright et al 2013).…”

Section: E674mentioning

confidence: 99%

The Ongoing Need for High-Resolution Regional Climate Models: Process Understanding and Stakeholder Information

Gutowski

Ullrich

Hall

et al. 2020

Bulletin of the American Meteorological Society

117

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Regional climate modeling addresses our need to understand and simulate climatic processes and phenomena unresolved in global models. This paper highlights examples of current approaches to and innovative uses of regional climate modeling that deepen understanding of the climate system. High-resolution models are generally more skillful in simulating extremes, such as heavy precipitation, strong winds, and severe storms. In addition, research has shown that fine-scale features such as mountains, coastlines, lakes, irrigation, land use, and urban heat islands can substantially influence a region’s climate and its response to changing forcings. Regional climate simulations explicitly simulating convection are now being performed, providing an opportunity to illuminate new physical behavior that previously was represented by parameterizations with large uncertainties. Regional and global models are both advancing toward higher resolution, as computational capacity increases. However, the resolution and ensemble size necessary to produce a sufficient statistical sample of these processes in global models has proven too costly for contemporary supercomputing systems. Regional climate models are thus indispensable tools that complement global models for understanding physical processes governing regional climate variability and change. The deeper understanding of regional climate processes also benefits stakeholders and policymakers who need physically robust, high-resolution climate information to guide societal responses to changing climate. Key scientific questions that will continue to require regional climate models, and opportunities are emerging for addressing those questions.

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“…The forecasts were verified for the 4 year period 2011–2014. Even though the forecast skill of mesoscale models has been evaluated in many studies globally (Coniglio et al , ; Schmidli et al , ; Marsh et al , ; Wen et al , ; Stratman et al , ; Berner et al , ), as well as over the Indian region (Rakesh et al , , , ; Goswami et al , ; Vishnu and Francis, ), very few studies have evaluated rainfall forecast skill for specific agricultural applications. Another important aspect of the present study is that the rainfall forecasts are verified against the observations at comparable resolution from the telemetric rain gauge (TRG) network installed and maintained by Karnataka State Natural Disaster Monitoring Centre (KSNDMC).…”

Section: Introductionmentioning

confidence: 99%

An evaluation strategy of skill of high‐resolution rainfall forecast for specific agricultural applications

Rakesh

Goswami

2016

Meteorological Applications

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ABSTRACT:A strategy for validation of rainfall forecasts for specific agricultural applications is presented. The focus is mainly on the design of specific forecast advisories that are risk-free and useful in spite of their inherent errors. The strategy works for these specific applications because the forecast advisories are based on when NOT to irrigate or apply fertilizer/pesticide because rain is predicted (risk-free because wrong forecast only delays irrigation/application of fertilizer/pesticide within tolerance). Thus, unlike in conventional forecast evaluation, a forecast is considered as valid if the forecasted rain (or no rain) is correct for the day of the forecast (D0C) or the next day or the day after (designated D1C and D2C, respectively), as the farmer can afford to postpone the field application for a couple of days beyond the scheduled date. The methodology has been evaluated for rainfall forecasts over Karnataka (a state in southwest India with nearly 56% of the workforce engaged in agriculture). Here, forecast validation against rain gauge observations is presented at comparable resolutions for the southwest (June to September) and the northeast (October to December) monsoon seasons during 2011-2014. Analyses demonstrate that forecasts over several areas which may appear to be less reliable based on conventional evaluation (D0C) are found to have useful skill for the specific agro-applications as evident from evaluation based on D1C and D2C criteria. Our analysis shows that the evaluation strategy presented is effective during the non-rainy (January-May) season also. It is pointed out that such an approach can help to meet the challenges in designing and implementing best practices in agriculture by combining immediate gains for the end users with long-term sustainability.

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Evaluation of High-Resolution WRF Model Simulations of Surface Wind over the West Coast of India

Cited by 11 publications

References 0 publications

On the understanding of very severe cyclone storm Ockhi with the WRF-ARW model

On the understanding of very severe cyclone storm Ockhi with the WRF-ARW model

The Ongoing Need for High-Resolution Regional Climate Models: Process Understanding and Stakeholder Information

An evaluation strategy of skill of high‐resolution rainfall forecast for specific agricultural applications

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