Martin Weißmann

3.1k total citations
68 papers, 1.7k citations indexed

About

Martin Weißmann is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Martin Weißmann has authored 68 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Atmospheric Science, 58 papers in Global and Planetary Change and 6 papers in Environmental Engineering. Recurrent topics in Martin Weißmann's work include Meteorological Phenomena and Simulations (60 papers), Climate variability and models (36 papers) and Atmospheric aerosols and clouds (25 papers). Martin Weißmann is often cited by papers focused on Meteorological Phenomena and Simulations (60 papers), Climate variability and models (36 papers) and Atmospheric aerosols and clouds (25 papers). Martin Weißmann collaborates with scholars based in Germany, Austria and United Kingdom. Martin Weißmann's co-authors include Florian Harnisch, Carla Cardinali, Oliver Reitebuch, Andreas Dörnbrack, Leonhard Scheck, Georg J. Mayr, Christian Keil, Tetsuo Nakazawa, Sim D. Aberson and Chun‐Chieh Wu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the Atmospheric Sciences and Monthly Weather Review.

In The Last Decade

Martin Weißmann

68 papers receiving 1.6k citations

Peers

Martin Weißmann

GPC

OCEAN

Alain Dabas France

Norman B. Wood United States

Alessandro Battaglia United Kingdom

Kevin R. Knupp United States

R. A. Kropfli United States

Thomas J. Greenwald United States

Wen-Chau Lee United States

Maria Cadeddu United States

Jaime Daniels United States

Ben Shipway United Kingdom

Alain Dabas France

Martin Weißmann

1.0k ×0.7

991 ×0.7

GPC

222 ×0.8

127 ×0.8

OCEAN

116 ×1.3

Citations per year, relative to Martin Weißmann Martin Weißmann (= 1×) peers Alain Dabas

Countries citing papers authored by Martin Weißmann

Since Specialization

Citations

This map shows the geographic impact of Martin Weißmann's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Martin Weißmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Weißmann more than expected).

Fields of papers citing papers by Martin Weißmann

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin Weißmann. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Martin Weißmann. The network helps show where Martin Weißmann may publish in the future.

Co-authorship network of co-authors of Martin Weißmann

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Weißmann. A scholar is included among the top collaborators of Martin Weißmann based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Martin Weißmann. Martin Weißmann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Weißmann, Martin, et al.. (2025). The synergy of assimilating visible and infrared radiances and radar observations. Quarterly Journal of the Royal Meteorological Society. 151(768). 2 indexed citations

Dance, Sarah L., Alison Fowler, David Simonin, et al.. (2025). On methods for assessment of the value of observations in convection‐permitting data assimilation and numerical weather forecasting. Quarterly Journal of the Royal Meteorological Society. 151(768). 1 indexed citations

Weißmann, Martin, et al.. (2025). Effects of Observation‐Operator Nonlinearity on the Assimilation of Visible and Infrared Radiances in Ensemble Data Assimilation. Quarterly Journal of the Royal Meteorological Society. 151(770). 1 indexed citations

Knippertz, Peter, et al.. (2024). Validation of Aeolus L2B products over the tropical Atlantic using radiosondes. Atmospheric measurement techniques. 17(2). 561–581. 3 indexed citations

Scheck, Leonhard, et al.. (2024). Diagnostics for Imbalance on the Convective Scale. Monthly Weather Review. 152(9). 2075–2088. 1 indexed citations

Miyoshi, Takemasa, et al.. (2023). Guidance on how to improve vertical covariance localization based on a 1000-member ensemble. Nonlinear processes in geophysics. 30(1). 13–29. 3 indexed citations

Weißmann, Martin, et al.. (2023). Ensemble‐based estimates of the impact of potential observations. Quarterly Journal of the Royal Meteorological Society. 149(754). 1546–1571. 2 indexed citations

Knippertz, Peter, et al.. (2023). Impact of Aeolus wind lidar observations on the representation of the West African monsoon circulation in the ECMWF and DWD forecasting systems. Quarterly Journal of the Royal Meteorological Society. 149(752). 933–958. 2 indexed citations

Weißmann, Martin, et al.. (2023). Investigation of links between dynamical scenarios and particularly high impact of Aeolus on numerical weather prediction (NWP) forecasts. Weather and Climate Dynamics. 4(1). 249–264. 12 indexed citations

10.

Krüger, Konstantin, Andreas Schäfler, Martin Wirth, Martin Weißmann, & George C. Craig. (2022). Vertical structure of the lower-stratospheric moist bias in the ERA5 reanalysis and its connection to mixing processes. Atmospheric chemistry and physics. 22(23). 15559–15577. 16 indexed citations

11.

Craig, George C., et al.. (2022). Distributions and convergence of forecast variables in a 1,000‐member convection‐permitting ensemble. Quarterly Journal of the Royal Meteorological Society. 148(746). 2325–2343. 14 indexed citations

12.

Knippertz, Peter, et al.. (2021). The Impact of Aeolus wind observations on the West African Monsoon. Repository KITopen (Karlsruhe Institute of Technology). 1 indexed citations

13.

Scheck, Leonhard, et al.. (2021). Understanding the model representation of clouds based on visible and infrared satellite observations. Atmospheric chemistry and physics. 21(16). 12273–12290. 19 indexed citations

14.

Weißmann, Martin, et al.. (2021). Validation of Aeolus winds using radiosonde observations and numerical weather prediction model equivalents. Atmospheric measurement techniques. 14(3). 2167–2183. 55 indexed citations

15.

Weißmann, Martin, et al.. (2020). Validation of Aeolus winds using radiosonde observations and NWP model equivalents. elib (German Aerospace Center). 1 indexed citations

16.

Scheck, Leonhard, et al.. (2020). Assimilating visible satellite images for convective‐scale numerical weather prediction: A case‐study. Quarterly Journal of the Royal Meteorological Society. 146(732). 3165–3186. 31 indexed citations

17.

Kostka, P., et al.. (2014). Observation Operator for Visible and Near-Infrared Satellite Reflectances. Journal of Atmospheric and Oceanic Technology. 31(6). 1216–1233. 33 indexed citations

18.

Weißmann, Martin, et al.. (2014). Height Correction of Atmospheric Motion Vectors Using Satellite Lidar Observations from CALIPSO. Journal of Applied Meteorology and Climatology. 53(7). 1809–1819. 16 indexed citations

19.

Harnisch, Florian & Martin Weißmann. (2010). Sensitivity of Typhoon Forecasts to Different Subsets of Targeted Dropsonde Observations. Monthly Weather Review. 138(7). 2664–2680. 39 indexed citations

20.

Weißmann, Martin, Andreas Dörnbrack, R. Calhoun, & Andreas Wieser. (2006). Dual Doppler lidar observations during T-REX. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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