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
Sampling and misspecification errors in the estimation of observation‐error covariance matrices using observation‐minus‐background and observation‐minus‐analysis statistics. 2024-07
DOI: https://doi.org/10.1002/qj.4750
A Novel Localized Fast Multipole Method for Computations With Spatially Correlated Observation Error Statistics in Data Assimilation. 2024-06
DOI: https://doi.org/10.1029/2023MS003871
Assessing the influence of observations on the analysis in ensemble-based data assimilation systems. 2024-03-08
DOI: https://doi.org/10.5194/egusphere-egu24-4082
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
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. 2023-01
DOI: https://doi.org/10.1002/asl.1130
Efficient computation of matrix‐vector products with full observation weighting matrices in data assimilation. 2021-09-23
ARXIV: http://dx.doi.org/10.1002/qj.4170
MATLAB code for the localized Singular Value Decomposition approach of the Fast Multipole Method (the local SVD-FMM). 2021
DOI: https://researchdata.reading.ac.uk/id/eprint/329
Evaluation of Daily Precipitation Extremes in Reanalysis and Gridded Observation‐Based Data Sets Over Germany. 2020-09-28
DOI: https://doi.org/10.1029/2020GL089624
Effects of stochastic parametrization on extreme value statistics. 2019-08
DOI: https://doi.org/10.1063/1.5095756
Data Assimilation in a Multi-Scale Model. 2017-12-20
