Dong-Jun Seo

Global and Planetary Change · 2004–2014

A researcher in the Science corpus: 5 papers; trusts 8 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Global and Planetary Change — 53 citations into it; #4,761 of 10,225 by trust here, #3,098 by citations
• Atmospheric Science — 40 citations into it
• Water Science and Technology — 33 citations into it; #669 of 1,711 by trust here, #494 by citations
• Environmental Engineering — 29 citations into it

Whom Dong-Jun Seo trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Tilmann Gneiting
2. Adrian E. Raftery

Who trusts Dong-Jun Seo overall

1. Weihua Li
2. Hoshin V. Gupta
3. Yuqiong Liu
4. A. Sankarasubramanian
5. Qingyun Duan
6. P. Pokhrel
7. Lihua Xiong
8. Xiaoli Jin

Papers from Dong-Jun Seo's perspective

Ordered by how strongly the researchers Dong-Jun Seo trusts endorse each paper. Same corpus, a different order for every researcher.

1. Bias and data assimilation
2. The future of distributed models: model calibration and uncertainty prediction.
3. Using Bayesian Model Averaging to Calibrate Forecast Ensembles
4. Probabilistic forecasts, calibration and sharpness
5. The rationale behind the success of multi-model ensembles in seasonal forecasting-II
6. The rationale behind the success of multi-model ensembles in seasonal forecasting — I. Basic concept
7. Towards a Bayesian total error analysis of conceptual rainfall-runoff models: Characterising model error using storm-dependent parameters
8. An integrated hydrologic Bayesian multimodel combination framework: Confronting input, parameter, and model structural uncertainty in hydrologic prediction
9. Towards the characterization of streamflow simulation uncertainty through multimodel ensembles
10. Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using the particle filter

Their papers

• Comparative evaluation of maximum likelihood ensemble filter and ensemble Kalman filter for real-time assimilation of streamflow data into operational hydrologic models (2014) — 48 citations
• Evaluation of a nonparametric post‐processor for bias correction and uncertainty estimation of hydrologic predictions (2013) — 62 citations
• Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities (2012) — 453 citations
• The distributed model intercomparison project (DMIP): Motivation and experiment design (2004) — 446 citations
• Towards the characterization of streamflow simulation uncertainty through multimodel ensembles (2004) — 355 citations