Previsões meteorológicas do Modelo Eta para subsidiar o uso de modelos de previsão agrícola no Centro-Sul do Brasil

Vieira, Pedro; Neto, Durval Dourado; Chou, Sin Chan; Martin, Thomas Newton

doi:10.1590/s0103-84782008005000076

Cited by 5 publications

(6 citation statements)

References 6 publications

(4 reference statements)

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“…As shown, the rRMSE values exceeded 50% (except for the 2010/2011 crop year), which indicates that the Eta measures are not very reliable for the analyzed period. Similar results showing overestimation in the Eta data for the Minas Gerais region was observed in [5]. According to the authors, the modeling errors may be associated with deficiencies in modeling elements of atmospheric circulation, elements of topography, surface coverage, and possible interactions between these elements.…”

Section: Coefficient Of Determinationsupporting

confidence: 65%

“…At large scales, remotely sensed data and numerical predictions have helped to overcome the lack of meteorological stations, serving as an alternative source of time series data on global and/or regional scales and enabling event detection and decision-making. However, these resources are rarely used in the agricultural sector [5,6].…”

Section: Introductionmentioning

confidence: 99%

“…Vieira Junior et al [5] pointed out not only that the Eta model usually over estimate rainfall in Minas Gerais, but also that random and systematic errors are related to regional characteristics. Franchito et al and Pereira et al [26,27] validated the accuracy of TRMM data over Brazil.…”

Section: Introductionmentioning

confidence: 99%

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Evaluating Precipitation Estimates from Eta, TRMM and CHRIPS Data in the South-Southeast Region of Minas Gerais State—Brazil

2018

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Precipitation estimates derived from the Eta model and from TRMM (Tropical Rainfall Measuring Mission) and CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) remotely sensed data were compared to the precipitation data of the INMET (National Institute of Meteorology) meteorological stations in the south-southeast region of Minas Gerais state, Brazil, in the period between July 2009 and June 2015. Then, information about evapotranspiration (ETR), water deficit (DEF), and water surplus (EXC) was obtained from the precipitation data, using the sequential water balance (SWB) separately for each type of precipitation data (INMET, TRMM, Eta, and CHIRPS). Subsequently, the components of the SWB were comparatively analyzed. The results indicate that all three products overestimate rainfall. The strongest relationships between the INMET data and the estimated data were observed for the TRMM, in terms of precipitation estimates, as well as DEF, EXC, and ETR components. The Eta precipitation estimates are overestimated relative to those from INMET, resulting in underestimation of the water deficit (DEF ETA) and overestimation of evapotranspiration (ETR ETA). In general, the CHIRPS data presented a pattern similar to the station data, though statistical analyses were lower than those of the TRMM data.

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Section: Coefficient Of Determinationsupporting

confidence: 65%

Section: Introductionmentioning

confidence: 99%

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Evaluating Precipitation Estimates from Eta, TRMM and CHRIPS Data in the South-Southeast Region of Minas Gerais State—Brazil

2018

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“…Para melhorar a resolução e previsão dos cenários futuros, utiliza-se a redução da resolução espacial, através do uso de modelo de mesoescala (técnica do "downscaling"). Esse modelo foi instalado no CPTEC em 1996 com a finalidade de complementar a Previsão Numérica de Tempo que vem sendo realizada operacionalmente desde o início de 1995, acoplado com o modelo de circulação geral atmosférica HadCM3 (Vieira Júnior et al, 2009).…”

Section: Introductionunclassified

Temperatura e precipitação: futuros cenários do município de Taubaté, SP, Brasil

Santos

Fisch

2016

Rev. ambiente água

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This work quantified temperature and precipitation variations in the region of Taubate using historic precipitation data and temperature simulations (climatology from 1961 to 1990). Corrections were made based on the observational data, and simulations of future time intervals (2011-2040, 2041-2070, 2071-2099) using a climate-model simulation. Thus, it is possible to predict an increase of 3.6°C in the average annual air temperature and an increase of 231 mm in annual accumulated rainfall (equivalent to approximately 17% of the climatological normal) for the interval 2071-2099. Moreover, in relation to seasonal distribution, there is a higher monthly average temperature increase in the spring (4.1°C) and lower in the summer (3.4°C) and a higher average daily increase in summer rainfall (1.1 mm) and smaller increase in spring (0.3 mm). There is also an increase of approximately 5 days in the daily number of days with greater than 1mm precipitation throughout the year. The analysis of the water balance showed deficits in the months of August and September and found a disparity between the input and output of water entering the territory through precipitation, evapotranspiration, and water consumption, suggesting the need to adapt to new social and environmental scenarios.

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“…Although the evaluation of these forecasts showed some level of error in various areas where corn crop is produced [49], the forecasts captured reasonably well the crop productivity forecasts, particularly in the months of maximum productivity.…”

Section: Topics In Climate Modeling 144mentioning

confidence: 90%

The Eta Model: Design, Use, and Added Value

Mesinger¹,

Veljovic²,

Chou³

et al. 2016

Topics in Climate Modeling

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The design of the Eta model goes back to early 1970s, when its original dynamical core was designed following the philosophy of Akio Arakawa of emulating important properties of the atmospheric governing equations. The core's later major features were invented and implemented in the mid-1980s. Once a comprehensive physics package was added, the model became operational as a regional NWP model in the United States in 1993. Its use for regional climate projections followed later, for the South American region and then for a regional reanalysis over the North American region. Summary of the model's dynamical core is given, followed by that of its physics package. Results of experiments revealing the model's ability to generate added value even at large scales when run as a regional climate model (RCM) are summarized. The Eta model is applied on various climate scales seamlessly, from subseasonal, seasonal to multidecadal, from coarse 40 km up to high 5 km resolution. Examples of applications to various socioeconomic sectors, such as for hydropower management, crop yield forecasts, environmental and forest conservation, urban areas management, assessment of natural disaster risks, etc., are given. The Eta RCM capability to reproduce extreme climatic values is pointed out.

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Previsões meteorológicas do Modelo Eta para subsidiar o uso de modelos de previsão agrícola no Centro-Sul do Brasil

Cited by 5 publications

References 6 publications

Evaluating Precipitation Estimates from Eta, TRMM and CHRIPS Data in the South-Southeast Region of Minas Gerais State—Brazil

Evaluating Precipitation Estimates from Eta, TRMM and CHRIPS Data in the South-Southeast Region of Minas Gerais State—Brazil

Temperatura e precipitação: futuros cenários do município de Taubaté, SP, Brasil

The Eta Model: Design, Use, and Added Value

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