David Walters

4.6k total citations
22 papers, 607 citations indexed

About

David Walters is a scholar working on Atmospheric Science, Global and Planetary Change and Earth-Surface Processes. According to data from OpenAlex, David Walters has authored 22 papers receiving a total of 607 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Atmospheric Science, 18 papers in Global and Planetary Change and 4 papers in Earth-Surface Processes. Recurrent topics in David Walters's work include Climate variability and models (14 papers), Atmospheric chemistry and aerosols (9 papers) and Atmospheric aerosols and clouds (8 papers). David Walters is often cited by papers focused on Climate variability and models (14 papers), Atmospheric chemistry and aerosols (9 papers) and Atmospheric aerosols and clouds (8 papers). David Walters collaborates with scholars based in United Kingdom, United States and Australia. David Walters's co-authors include Sean Milton, Jane P. Mulcahy, Steven J. Abel, Grant Allen, Nicolas Bellouin, Adrian Lock, A. R. Brown, John Edwards, Robert J. Beare and Robert R. King and has published in prestigious journals such as Journal of Climate, Monthly Weather Review and Atmospheric chemistry and physics.

In The Last Decade

David Walters

22 papers receiving 598 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David Walters United Kingdom 11 541 512 110 50 37 22 607
Alison Stirling United Kingdom 13 569 1.1× 605 1.2× 53 0.5× 18 0.4× 51 1.4× 31 677
Gary K. Greenhut United States 12 355 0.7× 311 0.6× 186 1.7× 37 0.7× 130 3.5× 40 545
Thomas Rose Germany 13 590 1.1× 478 0.9× 44 0.4× 37 0.7× 80 2.2× 28 694
K. Loukachine Italy 11 785 1.5× 825 1.6× 22 0.2× 19 0.4× 20 0.5× 23 913
Masahiro Sawada Japan 16 843 1.6× 724 1.4× 204 1.9× 12 0.2× 50 1.4× 42 917
Katrin Lonitz United Kingdom 8 605 1.1× 542 1.1× 55 0.5× 49 1.0× 36 1.0× 15 647
Chanh Kieu United States 20 969 1.8× 740 1.4× 421 3.8× 20 0.4× 30 0.8× 66 1.0k
Daniel Hernández‐Deckers Colombia 9 335 0.6× 392 0.8× 229 2.1× 24 0.5× 64 1.7× 18 503
Richard A Allard United States 15 491 0.9× 203 0.4× 271 2.5× 69 1.4× 14 0.4× 56 620
C.G. Dease United States 3 603 1.1× 634 1.2× 116 1.1× 9 0.2× 18 0.5× 4 723

Countries citing papers authored by David Walters

Since Specialization
Citations

This map shows the geographic impact of David Walters'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 David Walters with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Walters more than expected).

Fields of papers citing papers by David Walters

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Walters. 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 David Walters. The network helps show where David Walters may publish in the future.

Co-authorship network of co-authors of David Walters

This figure shows the co-authorship network connecting the top 25 collaborators of David Walters. A scholar is included among the top collaborators of David Walters 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 David Walters. David Walters is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Tomassini, Lorenzo, Martin Willett, Alistair Sellar, et al.. (2023). Confronting the Convective Gray Zone in the Global Configuration of the Met Office Unified Model. Journal of Advances in Modeling Earth Systems. 15(5). 12 indexed citations
2.
Inverarity, Gordon, Warren Tennant, L. Anton, et al.. (2023). Met Office MOGREPS‐G initialisation using an ensemble of hybrid four‐dimensional ensemble variational (En‐4DEnVar) data assimilations. Quarterly Journal of the Royal Meteorological Society. 149(753). 1138–1164. 10 indexed citations
3.
Porson, Aurore, Joanne M. Carr, Susanna Hagelin, et al.. (2020). Recent upgrades to the Met Office convective‐scale ensemble: An hourly time‐lagged 5‐day ensemble. Quarterly Journal of the Royal Meteorological Society. 146(732). 3245–3265. 28 indexed citations
4.
Maynard, Christopher & David Walters. (2019). Mixed-precision arithmetic in the ENDGame dynamical core of the Unified Model, a numerical weather prediction and climate model code. Computer Physics Communications. 244. 69–75. 8 indexed citations
5.
Oh, Jiyoung, Seok‐Woo Son, K. D. Williams, et al.. (2018). Ozone sensitivity of tropical upper‐troposphere and stratosphere temperature in the MetOffice Unified Model. Quarterly Journal of the Royal Meteorological Society. 144(715). 2001–2009. 9 indexed citations
6.
Baran, Anthony J., Peter Hill, David Walters, et al.. (2016). The Impact of Two Coupled Cirrus Microphysics–Radiation Parameterizations on the Temperature and Specific Humidity Biases in the Tropical Tropopause Layer in a Climate Model. Journal of Climate. 29(14). 5299–5316. 30 indexed citations
7.
Rae, Jamie, Helene T. Hewitt, Ann Keen, et al.. (2015). Development of the Global Sea Ice 6.0 CICE configuration for the Met Office Global Coupled model. Geoscientific model development. 8(7). 2221–2230. 77 indexed citations
8.
Rae, Jamie, Helene T. Hewitt, Ann Keen, et al.. (2015). Development of Global Sea Ice 6.0 CICE configuration for the Met Office Global Coupled Model. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 10 indexed citations
9.
Lea, Daniel J., Isabelle Mirouze, Matthew Martin, et al.. (2015). Assessing a New Coupled Data Assimilation System Based on the Met Office Coupled Atmosphere–Land–Ocean–Sea Ice Model. Monthly Weather Review. 143(11). 4678–4694. 90 indexed citations
10.
Mulcahy, Jane P., David Walters, Nicolas Bellouin, & Sean Milton. (2014). Impacts of increasing the aerosol complexity in the Met Office global numerical weather prediction model. Atmospheric chemistry and physics. 14(9). 4749–4778. 66 indexed citations
11.
Mulcahy, Jane P., David Walters, Nicolas Bellouin, & Sean Milton. (2013). Impacts of increasing the aerosol complexity in the Met Office global NWP model. 2 indexed citations
12.
Ackerley, Duncan, Manoj Joshi, E. J. Highwood, et al.. (2012). A Comparison of Two Dust Uplift Schemes within the Same General Circulation Model. Advances in Meteorology. 2012. 1–13. 5 indexed citations
13.
Haywood, Jim, Ben Johnson, S. Osborne, et al.. (2011). Motivation, rationale and key results from the GERBILS Saharan dust measurement campaign. Quarterly Journal of the Royal Meteorological Society. 137(658). 1106–1116. 39 indexed citations
14.
Johnson, Ben, M. E. Brooks, David Walters, et al.. (2011). Assessment of the Met Office dust forecast model using observations from the GERBILS campaign. Quarterly Journal of the Royal Meteorological Society. 137(658). 1131–1148. 26 indexed citations
15.
Abel, Steven J., David Walters, & Grant Allen. (2010). Evaluation of stratocumulus cloud prediction in the Met Office forecast model during VOCALS-REx. Atmospheric chemistry and physics. 10(21). 10541–10559. 52 indexed citations
16.
Abel, Steven J., David Walters, & Grant Allen. (2010). Evaluation of stratocumulus cloud prediction in the Met Office forecast model during VOCALS-REx. 3 indexed citations
17.
Ackerley, Duncan, E. J. Highwood, Mark A. Harrison, et al.. (2009). The development of a new dust uplift scheme in the Met Office Unified Model™. Meteorological Applications. 16(4). 445–460. 5 indexed citations
18.
Brown, A. R., Robert J. Beare, John Edwards, et al.. (2008). Upgrades to the Boundary-Layer Scheme in the Met Office Numerical Weather Prediction Model. Boundary-Layer Meteorology. 128(1). 117–132. 110 indexed citations
19.
Walters, David & Simon Hands. (2005). The Lattice NJL Model at Non-zero Baryon and Isospin Densities. Nuclear Physics B - Proceedings Supplements. 140. 532–534. 2 indexed citations
20.
Hands, Simon & David Walters. (2004). Numerical portrait of a relativistic BCS gapped superfluid. Physical review. D. Particles, fields, gravitation, and cosmology. 69(7). 17 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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