Peitao Peng

3.4k total citations · 1 hit paper
28 papers, 2.1k citations indexed

About

Peitao Peng is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, Peitao Peng has authored 28 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Atmospheric Science, 25 papers in Global and Planetary Change and 12 papers in Oceanography. Recurrent topics in Peitao Peng's work include Climate variability and models (24 papers), Meteorological Phenomena and Simulations (22 papers) and Oceanographic and Atmospheric Processes (9 papers). Peitao Peng is often cited by papers focused on Climate variability and models (24 papers), Meteorological Phenomena and Simulations (22 papers) and Oceanographic and Atmospheric Processes (9 papers). Peitao Peng collaborates with scholars based in United States, China and Australia. Peitao Peng's co-authors include Arun Kumar, Anthony G. Barnston, Shrinivas Moorthi, W. Wang, Arun Kumar, Huug M. van den Dool, Hua Pan, Diane Stokes, P. Xie and Sudhir Nadiga and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Journal of Climate and Geophysical Research Letters.

In The Last Decade

Peitao Peng

28 papers receiving 2.0k citations

Hit Papers

The NCEP Climate Forecast System 2006 2026 2012 2019 2006 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peitao Peng United States 18 1.9k 1.8k 808 104 98 28 2.1k
Craig MacLachlan United Kingdom 25 2.2k 1.1× 2.0k 1.2× 757 0.9× 129 1.2× 82 0.8× 39 2.4k
Čedo Branković United Kingdom 24 2.0k 1.0× 1.9k 1.1× 527 0.7× 133 1.3× 112 1.1× 47 2.2k
Leon Hermanson United Kingdom 24 2.0k 1.0× 1.7k 1.0× 754 0.9× 74 0.7× 63 0.6× 58 2.1k
Nicholas P. Klingaman United Kingdom 30 2.3k 1.2× 2.0k 1.1× 889 1.1× 78 0.8× 135 1.4× 98 2.4k
W. Wang United States 7 1.4k 0.7× 1.3k 0.7× 555 0.7× 67 0.6× 65 0.7× 10 1.5k
Mio Matsueda Japan 19 1.6k 0.8× 1.6k 0.9× 285 0.4× 89 0.9× 114 1.2× 45 1.8k
Romain Roehrig France 24 1.7k 0.9× 1.6k 0.9× 347 0.4× 85 0.8× 52 0.5× 66 1.9k
Rosie Eade United Kingdom 24 2.6k 1.4× 2.4k 1.3× 984 1.2× 75 0.7× 83 0.8× 40 2.8k
Mischa Croci‐Maspoli Switzerland 23 2.1k 1.1× 2.1k 1.2× 315 0.4× 66 0.6× 87 0.9× 32 2.4k
P. A. Francis India 18 1.2k 0.6× 975 0.5× 565 0.7× 101 1.0× 63 0.6× 49 1.4k

Countries citing papers authored by Peitao Peng

Since Specialization
Citations

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

Fields of papers citing papers by Peitao Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peitao Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Peitao Peng. A scholar is included among the top collaborators of Peitao Peng 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 Peitao Peng. Peitao Peng 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.
Kumar, Arun, et al.. (2024). Why Do DJF 2023/24 Upper‐Level 200‐hPa Geopotential Height Forecasts Look Different From the Expected El Niño Response?. Geophysical Research Letters. 51(14). 2 indexed citations
2.
Peng, Peitao, Wanqiu Wang, & Arun Kumar. (2023). Seasonal Tropical–Extratropical Teleconnections Originating from Tropical Rainfall Modes Independent of the Niño-3.4 Index in Northern Winters. Journal of Climate. 36(17). 5713–5728. 2 indexed citations
3.
Bhatt, Uma S., Peter A. Bieniek, Robert Ziel, et al.. (2021). Evaluation of Seasonal Forecasts for the Fire Season in Interior Alaska. Weather and Forecasting. 36(2). 601–613. 7 indexed citations
4.
Hu, Zeng‐Zhen, Arun Kumar, Jieshun Zhu, Peitao Peng, & Bohua Huang. (2018). On the Challenge for ENSO Cycle Prediction: An Example from NCEP Climate Forecast System, Version 2. Journal of Climate. 32(1). 183–194. 39 indexed citations
5.
Peng, Peitao, Arun Kumar, Mingyue Chen, Zeng‐Zhen Hu, & Bhaskar Jha. (2018). Was the North American extreme climate in winter 2013/14 a SST forced response?. Climate Dynamics. 52(5-6). 3099–3110. 14 indexed citations
6.
Peng, Peitao, Arun Kumar, & Zeng‐Zhen Hu. (2017). What drove the Pacific and North America climate anomalies in winter 2014/15?. Climate Dynamics. 51(7-8). 2667–2679. 17 indexed citations
7.
Kumar, Arun, Zeng‐Zhen Hu, Bhaskar Jha, & Peitao Peng. (2016). Estimating ENSO predictability based on multi-model hindcasts. Climate Dynamics. 48(1-2). 39–51. 46 indexed citations
8.
Wang, Hui, Zeng‐Zhen Hu, Arun Kumar, et al.. (2016). An Assessment of Multimodel Simulations for the Variability of Western North Pacific Tropical Cyclones and Its Association with ENSO. Journal of Climate. 29(18). 6401–6423. 30 indexed citations
9.
Si, Dong, Zeng‐Zhen Hu, Arun Kumar, et al.. (2015). Is the interdecadal variation of the summer rainfall over eastern China associated with SST?. Climate Dynamics. 46(1-2). 135–146. 15 indexed citations
10.
Liu, Yunyun, Zeng‐Zhen Hu, Arun Kumar, et al.. (2014). Tropospheric biennial oscillation of summer monsoon rainfall over East Asia and its association with ENSO. Climate Dynamics. 45(7-8). 1747–1759. 15 indexed citations
11.
Peng, Peitao, Arun Kumar, & Bhaskar Jha. (2014). Climate mean, variability and dominant patterns of the Northern Hemisphere wintertime mean atmospheric circulation in the NCEP CFSv2. Climate Dynamics. 42(9-10). 2783–2799. 10 indexed citations
12.
Peng, Peitao, Anthony G. Barnston, & Arun Kumar. (2012). A Comparison of Skill between Two Versions of the NCEP Climate Forecast System (CFS) and CPC’s Operational Short-Lead Seasonal Outlooks. Weather and Forecasting. 28(2). 445–462. 36 indexed citations
13.
Peng, Peitao, Arun Kumar, Michael S. Halpert, & Anthony G. Barnston. (2012). An Analysis of CPC’s Operational 0.5-Month Lead Seasonal Outlooks. Weather and Forecasting. 27(4). 898–917. 43 indexed citations
14.
Peng, Peitao, Arun Kumar, & W. Wang. (2009). An analysis of seasonal predictability in coupled model forecasts. Climate Dynamics. 36(3-4). 637–648. 65 indexed citations
15.
Peng, Peitao, et al.. (2007). Sea surface temperature variations in the southwestern South China Sea over the past 160 ka. 26(2). 2 indexed citations
16.
Saha, Subodh Kumar, Sudhir Nadiga, W. Wang, et al.. (2006). The NCEP Climate Forecast System. Journal of Climate. 19(15). 3483–3517. 957 indexed citations breakdown →
17.
Peng, Peitao, et al.. (2005). Variability, predictability and prediction of DJF climate in NCEP Climate Forecast System (CFS). AGU Spring Meeting Abstracts. 2005. 4 indexed citations
18.
Kumar, Arun, Qin Zhang, Peitao Peng, & Bhaskar Jha. (2005). SST-Forced Atmospheric Variability in an Atmospheric General Circulation Model. Journal of Climate. 18(19). 3953–3967. 28 indexed citations
19.
Peng, Peitao, Arun Kumar, Huug van den Dool, & Anthony G. Barnston. (2002). An analysis of multimodel ensemble predictions for seasonal climate anomalies. Journal of Geophysical Research Atmospheres. 107(D23). 99 indexed citations
20.
Peng, Peitao. (1995). Dynamics of Stationary Wave Anomalies Associated with ENSO in the Cola GCM.. PhDT. 5 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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