Jan-Peter Schulz

1.1k total citations
24 papers, 354 citations indexed

About

Jan-Peter Schulz is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Jan-Peter Schulz has authored 24 papers receiving a total of 354 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Atmospheric Science, 12 papers in Global and Planetary Change and 6 papers in Environmental Engineering. Recurrent topics in Jan-Peter Schulz's work include Meteorological Phenomena and Simulations (7 papers), Climate variability and models (6 papers) and Urban Heat Island Mitigation (5 papers). Jan-Peter Schulz is often cited by papers focused on Meteorological Phenomena and Simulations (7 papers), Climate variability and models (6 papers) and Urban Heat Island Mitigation (5 papers). Jan-Peter Schulz collaborates with scholars based in Germany, Italy and Switzerland. Jan-Peter Schulz's co-authors include L. Dümenil, Jan Polcher‬, Martin Wild, Stefan Hagemann, Philipp de Vrese, Péter Bauer, Hartmut Graßl, Bodo Ahrens, Peter Schluessel and Steffen Kothe and has published in prestigious journals such as Bulletin of the American Meteorological Society, Climate Dynamics and Boundary-Layer Meteorology.

In The Last Decade

Jan-Peter Schulz

22 papers receiving 335 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jan-Peter Schulz Germany 10 269 266 81 53 26 24 354
Marcelino Q. Villafuerte Philippines 10 371 1.4× 300 1.1× 35 0.4× 67 1.3× 33 1.3× 17 436
Muhammad Mubashar Dogar Japan 15 411 1.5× 319 1.2× 71 0.9× 91 1.7× 31 1.2× 34 489
P. Drobinski France 9 342 1.3× 367 1.4× 91 1.1× 37 0.7× 28 1.1× 13 461
Kwinten Van Weverberg Belgium 15 597 2.2× 601 2.3× 97 1.2× 25 0.5× 18 0.7× 33 689
Gregor Skok Slovenia 13 369 1.4× 392 1.5× 66 0.8× 53 1.0× 20 0.8× 31 478
Hongping Gu China 6 174 0.6× 156 0.6× 48 0.6× 36 0.7× 57 2.2× 13 229
Chunhui Lu China 14 384 1.4× 306 1.2× 54 0.7× 47 0.9× 23 0.9× 18 426
Xian Zhu China 12 302 1.1× 223 0.8× 56 0.7× 31 0.6× 62 2.4× 34 365
Wenshi Lin China 14 426 1.6× 470 1.8× 144 1.8× 53 1.0× 14 0.5× 55 591
Peter Dobrohotoff Australia 6 270 1.0× 202 0.8× 23 0.3× 93 1.8× 30 1.2× 7 347

Countries citing papers authored by Jan-Peter Schulz

Since Specialization
Citations

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

Fields of papers citing papers by Jan-Peter Schulz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jan-Peter Schulz. 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 Jan-Peter Schulz. The network helps show where Jan-Peter Schulz may publish in the future.

Co-authorship network of co-authors of Jan-Peter Schulz

This figure shows the co-authorship network connecting the top 25 collaborators of Jan-Peter Schulz. A scholar is included among the top collaborators of Jan-Peter Schulz 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 Jan-Peter Schulz. Jan-Peter Schulz 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.
Denissen, Jasper, Sarah Keeley, Peter Dueben, et al.. (2025). Numerical Weather Prediction Model Coupling—Strategies, Challenges, and Outlook. Bulletin of the American Meteorological Society. 107(1). E183–E189.
2.
Adinolfi, Marianna, et al.. (2025). Investigating urban heat islands over Rome and Milan during a summer period through the TERRA_URB parameterization in the ICON model. Urban Climate. 60. 102335–102335. 1 indexed citations
3.
4.
Garbero, Valeria, Massimo Milelli, Edoardo Bucchignani, et al.. (2021). Evaluating the Urban Canopy Scheme TERRA_URB in the COSMO Model for Selected European Cities. Atmosphere. 12(2). 237–237. 21 indexed citations
5.
Hartmann, E., et al.. (2020). Impact of Environmental Conditions on Grass Phenology in the Regional Climate Model COSMO-CLM. Atmosphere. 11(12). 1364–1364. 3 indexed citations
6.
7.
Schulz, Jan-Peter, et al.. (2020). Improving the Processes in the Land Surface Scheme TERRA: Bare Soil Evaporation and Skin Temperature. Atmosphere. 11(5). 513–513. 35 indexed citations
8.
Shrestha, Prabhakar, Wolfgang Kurtz, Jan-Peter Schulz, et al.. (2018). Connection Between Root Zone Soil Moisture and Surface Energy Flux Partitioning Using Modeling, Observations, and Data Assimilation for a Temperate Grassland Site in Germany. Journal of Geophysical Research Biogeosciences. 123(9). 2839–2862. 23 indexed citations
9.
Schulz, Jan-Peter, et al.. (2016). An evaluation of the simulated bare soil evaporation of an atmospheric model. EGU General Assembly Conference Abstracts. 2 indexed citations
10.
Schulz, Jan-Peter, et al.. (2016). Evaluation of the ground heat flux simulated by a multi-layer land surface scheme using high-quality observations at grass land and bare soil. Meteorologische Zeitschrift. 25(5). 607–620. 41 indexed citations
11.
Vrese, Philipp de, Jan-Peter Schulz, & Stefan Hagemann. (2016). On the Representation of Heterogeneity in Land-Surface–Atmosphere Coupling. Boundary-Layer Meteorology. 160(1). 157–183. 28 indexed citations
12.
Schulz, Jan-Peter, et al.. (2015). Evaluation of the ground heat flux simulated by a multi-layer land surface scheme using high-quality observations at grass land and bare soil. EGU General Assembly Conference Abstracts. 6549. 2 indexed citations
13.
Schulz, Jan-Peter, et al.. (2014). A new leaf phenology for the land surface scheme TERRA of the COSMO atmospheric model. EGU General Assembly Conference Abstracts. 6852. 1 indexed citations
14.
Mironov, Dmitrii, et al.. (2012). Parameterisation of sea and lake ice in numerical weather prediction models of the German Weather Service. Tellus A Dynamic Meteorology and Oceanography. 64(1). 17330–17330. 31 indexed citations
15.
Schulz, Jan-Peter. (2011). Introducing a sea ice scheme in the COSMO model. 2 indexed citations
16.
Mieruch, Sebastian, Maximilian Reuter, H. Bovensmann, et al.. (2008). Global Water Vapor Trends From Satellite Data Compared With Radiosonde Measurements. AGU Fall Meeting Abstracts. 2008. 1 indexed citations
17.
Christensen, Jens Hesselbjerg, Ole B. Christensen, Jan-Peter Schulz, Stefan Hagemann, & Michael Botzet. (2001). High resolution physiographic data set for HIRHAM4: An application to a 50 km horizontal resolution domain covering Europe. 19 indexed citations
18.
Schulz, Jan-Peter, L. Dümenil, & Jan Polcher‬. (2001). On the Land Surface–Atmosphere Coupling and Its Impact in a Single-Column Atmospheric Model. Journal of Applied Meteorology. 40(3). 642–663. 45 indexed citations
19.
Roesch, Andreas, Jan-Peter Schulz, & Martin Wild. (1997). Comparison and sensitivity studies of the land-surface schemes in the ECHAM General Circulation Model and the Europa-Model. MPG.PuRe (Max Planck Society). 1 indexed citations
20.
Grossmann, K. U., et al.. (1994). Lower thermospheric infra-red emissions from minor species during high-latitude twilight—A. Experimental results. Journal of Atmospheric and Terrestrial Physics. 56(13-14). 1885–1897. 8 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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