Our People

Guannan Hu

Postdoctoral Research Assistant
Data Assimilation

Research interests

I am interested in data assimilation and observation impacts in numerical weather prediction. I work on improving the speed and accuracy of data assimilation, and assessing the impact of different observation types, which will help improve the accuracy of weather forecasts.

Recent publications

Assessing the Influence of Observations in Ensemble‐Based Data Assimilation Systems. 2025-11

DOI: https://doi.org/10.1029/2024MS004809

On methods for assessment of the value of observations in convection‐permitting data assimilation and numerical weather forecasting. 2025-04

DOI: https://doi.org/10.1002/qj.4933

Assessing the influence of observations on the analysis in ensemble-based data assimilation systems. 2025-01-20

DOI: https://doi.org/10.5194/egusphere-egu24-4082

A Novel Localized Fast Multipole Method for Computations With Spatially Correlated Observation Error Statistics in Data Assimilation. 2024

https://www.scopus.com/inward/record.url?eid=2-s2.0-85195604914&partnerID=MN8TOARS

Sampling and misspecification errors in the estimation of observation-error covariance matrices using observation-minus-background and observation-minus-analysis statistics. 2024

https://www.scopus.com/inward/record.url?eid=2-s2.0-85193576275&partnerID=MN8TOARS

A Novel Numerical Approximation Method for Computations with Spatially Correlated Observation Error Statistics in Data Assimilation. 2023-05-15

DOI: https://doi.org/10.5194/egusphere-egu23-14476

On methods for assessment of the influence and impact of observations in convection-permitting numerical weather prediction. 2023

https://www.scopus.com/inward/record.url?eid=2-s2.0-85174130339&partnerID=MN8TOARS

Progress, challenges, and future steps in data assimilation for convection-permitting numerical weather prediction: Report on the virtual meeting held on 10 and 12 November 2021. 2023

https://www.scopus.com/inward/record.url?eid=2-s2.0-85137574924&partnerID=MN8TOARS

Efficient computation of matrix‐vector products with full observation weighting matrices in data assimilation. 2021-09-23

ARXIV: http://arxiv.org/abs/2109.02091v1 DOI: https://doi.org/10.1002/qj.4170 ISSN: https://portal.issn.org/resource/ISSN/0035-9009 ISSN: https://portal.issn.org/resource/ISSN/1477-870X

Efficient computation of matrix-vector products with full observation weighting matrices in data assimilation. 2021

https://www.scopus.com/inward/record.url?eid=2-s2.0-85171313762&partnerID=MN8TOARS

MATLAB code for the localized Singular Value Decomposition approach of the Fast Multipole Method (the local SVD-FMM). 2021

DOI: https://doi.org/10.17864/1947.329

Evaluation of Daily Precipitation Extremes in Reanalysis and Gridded Observation-Based Data Sets Over Germany. 2020

https://www.scopus.com/inward/record.url?eid=2-s2.0-85091492874&partnerID=MN8TOARS

Effects of stochastic parametrization on extreme value statistics. 2019-08

DOI: https://doi.org/10.1063/1.5095756

Effects of stochastic parametrization on extreme value statistics. 2019