• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.1-12
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• 2000

We explore the structure and usefulness of CERES plot as a basic tool for dealing with curvature as a function of the new predictor in nonlinear regression. If a predictor has a nonlinear effect and there are nonlinear relationships among the predictors the partial residual plot and augmented partial residual plot are not able to display the correct functional form of the predictor. Unlike these plots the CERES plot can show the correct from. In situations where nonlinearity exists in two predictors we extend the idea of CERES plot to three dimensions, This is illustrated by simulated data.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.575-582
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• 2004

We explore the structure and usefulness of CERES plot as a basic tool for dealing with curvature as a function of the new predictor in generalized linear models. If a predictor has a nonlinear effect and there are nonlinear relationships among the predictors, the partial residual plot and augmented partial residual plot are not able to display the correct functional form of the predictor. Unlike these plots, the CERES plot can show the correct form. This is illustrated by simulated data.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.282-290
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• 2013

Biophysical and biochemical processes through which crops interact with the atmosphere have been simulated using land surface models and crop growth models. The Noah Multi Physics (MP) model and the CERES-Rice model, which are a land surface model, and a crop growth model, respectively, were used to simulate and compare rice growth and evapotranspiration (ET) in the areas near Haenam flux tower in Korea. Simulations using these models were performed from 2003 to 2012 during which flux measurements were obtained at the Haenam site. The Noah MP model failed to simulate the pattern of temporal change in leaf area index (LAI) after heading. The simulated aboveground biomass with the Noah MP model was underestimated by about 10% of the actual biomass. The ET simulated with the Noah MP model was as low as 21% of those with the CERES-Rice model. In comparison with actual ET measured at Haenam flux site, the root mean square error (RMSE) of the Noah MP model was 1.8 times larger than that of the CERES-Rice model. The Noah MP model seems to show less reliable simulation of crop growth and ET due to simplified phenology processes and assimilates partitioning compared with the CERES-Rice model. When ET was adjusted by the ratio between leaf biomass simulated using CERES-Rice model and Noah MP model, however, the RMSE of ET was reduced by 30%. This suggests that an improvement of the Noah MP model in representing rice growth in paddy fields would allow more reliable simulation of matter and energy fluxes.

• 한국데이터정보과학회:학술대회논문집
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• 2003.10a
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• pp.93-100
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• 2003

It is necessary to check the curvature of selected covariates in regression diagnostics. There are various graphical methods using residual plots based on least squares fitting. The sensitivity of LS fitting to outliers can distort their residuals, making the identification of the unknown function difficult to impossible. In this paper, we compare combining conditional expectation and residual plots(CERES Plots) between least square fit and robust fits using Huber M-estimator. Robust CERES will be far less distorted than their LS counterparts in the presence of outliers and hence, will be more useful in identifying the unknown function.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.169-176
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• 2008

We explore the structure and usefulness of three dimensional CERES plot as a basic tool for dealing with curvature as a function of the new predictors in generalized linear models. If predictors have nonlinear effects and there are nonlinear relationships among the predictors, the partial residual plot is not able to display the correct functional form of the predictors. Unlike this plots, the CERES plot can show the correct form. This is illustrated by simulated data.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.6
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• pp.509-519
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• 2017

Crop simulation models are valuable tools for estimating crop yield, environmental factors and management practices. The objective of this study was to evaluate the effect of soil types on barley productivity using CERES (Crop Environment REsource Synthesis)-barley, cropping system model. So the behavior of the model under various soil types and climatic conditions was evaluated. The results of the sensitivity analysis in temperature, $CO_2$, and precipitation showed that soil types had a direct impact on the simulated yield of CERES-barley model. We found that barley yield in clay soils would be more sensitive to precipitation and $CO_2$ in comparison with temperature. And the model showed limited accuracy in simulating water and nitrogen stress index for soil types. In general, the barley grown on clay soils were less sensitive to water stress than those grown on sandy soils. Especially it was found that the CERES model underestimated the effect of water stress in high precipitation which led to overprediction of crop yield in clay soils. In order to solve these problems and successfully forecast grain yield, further studies on the modification of the water stress response of crops should be considered prior to use of the CERES-barley model for yield forecasting.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.201-220
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• 2016

In this study, the net solar radiation fluxes at the surface are retrieved by updating an existing algorithm to be applicable for MODerate resolution Imaging Spectroradiometer (MODIS) observations, in which linear relationships between the solar radiation reflected from the top of atmosphere and the net surface solar radiation are employed. The results of this study have been evaluated through intercomparison with existing Clouds and the Earth's Radiant Energy System (CERES) data products and ground-based data from pyranometers at Gangneung-Wonju National University (GWNU) and the Southern Great Plains (SGP) of observatory of Atmospheric Radiation Measurement (ARM) site. Prior to the comparison of the surface radiation energy in relation to the energy balance of the earth, the radiation energy of the upper part of the atmosphere was compared. As a result, the coefficient of determination was over 0.9, showing considerable similarity, but the Root-Mean-Square-Deviation (RMSD) value was somewhat different, and the downward and net solar-radiation energy also showed similar results. The surface solar radiation data measured from pyranometers at Gangneung-Wonju National University (GWNU) and Atmospheric Radiation Measurement (ARM) observatory are used to validate the solar radiation data produced in this study. When compared to the GWNU, The results of this study show smaller RMSD values than CERES data, showing slightly better agreements with the surface data. On the other hand, when compared with the data from ARM SGP observatory, the results of this study bear slightly larger RMSD values than those for CERES. The downward and net solar radiation estimated by the algorithm of this study at a high spatial resolution are expected to be very useful in the near future after refinements on the identified problems, especially for those area without ground measurements of solar radiation.

• Proceedings of the Korean Society of Crop Science Conference
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• 1998.04a
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• pp.129-130
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• 1998

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.312-319
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• 2013

Our understanding of the sensitivities of crop responses to changes in carbon dioxide, temperature, and water is limited, which makes it difficult to fully utilize crop models in assessing the impact of climate change on future agricultural production. Genetic coefficients of CERES-Barley model for major domestic cultivars in South Korea (Olbori at Suwon, Albori at Milyang, Saessalbori at Iksan, and Samdobori at Jinju) were estimated from the observed data for daily weather and field trials for more than 10 years by using GenCalc in DSSAT. Data from 1997-2002 annual crop status report (Rural Development Administration, RDA) were used to validate the crop coefficients. The sitecalibrated CERES-Barley model was used to perform crop growth simulation with the 99 treatments of step change combinations in temperature, precipitation and carbon dioxide concentration with respect to the baseline climate (1981-2010) at four sites. The upper boundary corresponds to the 2071-2100 climate outlook from the RCP 8.5 scenario. The response surface of grain yield showed a distinct pattern of model behavior under the combined change in environmental variables. The simulated grain yield was most sensitive to $CO_2$ concentration, least sensitive to precipitation, and showing a variable response to temperature depending on cultivar. The emulated impacts of response surfaces are expected to facilitate assessment of projected climate impacts on a given cultivar in South Korea.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1191-1208
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• 2015

Most statistical methods are dependent on the summary statistic. However, with graphical approaches, it is easier to identify the characteristics of the data and detect information that cannot be obtained by the summary statistic. We present various graphical methods to assess the adequacy of models in logistic regression that include checking log-density ratio, structural dimension, marginal model plot, chi-residual plot, and CERES plot. Through simulation data, we investigate and compare the results of graphical approaches under diverse conditions.