The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Assessment of GPM-IMERG and Other Precipitation Products against Gauge Data under Different Topographic and Climatic Conditions in Iran: Preliminary Results
Open accessAbstract
The new generation of weather observatory satellites, namely Global Precipitation Measurement (GPM) constellation satellites, is the lead observatory of the 10 highly advanced earth orbiting weather research satellites. Indeed, GPM is the first satellite that has been designed to measure light rain and snowfall, in addition to heavy tropical rainfall. This work compares the final run of the Integrated Multi-satellitE Retrievals for GPM (IMERG) product, the post real time of TRMM and Multi-satellite Precipitation Analysis (TMPA-3B42) and the Era-Interim product from the European Centre for Medium Range Weather Forecasts (ECMWF) against the Iran Meteorological Organization (IMO) daily precipitation measured by the synoptic rain-gauges over four regions with different topography and climate conditions in Iran. Assessment is implemented for a one-year period from March 2014 to February 2015. Overall, in daily scale the results reveal that all three products lead to underestimation but IMERG performs better than other products and underestimates precipitation slightly in all four regions. Based on monthly and seasonal scale, in Guilan all products, in Bushehr and Kermanshah ERA-Interim and in Tehran IMERG and ERA-Interim tend to underestimate. The correlation coefficient between IMERG and the rain-gauge data in daily scale is far superior to that of Era-Interim and TMPA-3B42. On the basis of daily timescale of bias in comparison with the ground data, the IMERG product far outperforms ERA-Interim and 3B42 products. According to the categorical verification technique in this study, IMERG yields better results for detection of precipitation events on the basis of Probability of Detection (POD), Critical Success Index (CSI) and False Alarm Ratio (FAR) in those areas with stratiform and orographic precipitation, such as Tehran and Kermanshah, compared with other satellite/model data sets. In particular, for heavy precipitation (>15 mm/day), IMERG is superior to the other products in all study areas and could be used in future for meteorological and hydrological models, etc.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The ERA‐Interim reanalysis: configuration and performance of the data assimilation system
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., et al. (2011) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.828 · Cited by 24,480
Statistical Methods in the Atmospheric Sciences
Ramsey, P. H. (1996) · Technometrics · doi:10.1080/00401706.1996.10484553 · Cited by 7,601
Huffman, G. J., Bolvin, D. T., Nelkin, E. J., Wolff, D. B., Adler, R. F., Gu, G., Hong, Y., Bowman, K. P., & Stocker, E. F. (2007) · Journal of Hydrometeorology · doi:10.1175/jhm560.1 · Cited by 6,767
Mitchell, T. D., & Jones, P. D. (2005) · International Journal of Climatology · doi:10.1002/joc.1181 · Cited by 3,822
The Global Precipitation Measurement Mission
Hou, A. Y., Kakar, R. K., Neeck, S., Azarbarzin, A. A., Kummerow, C. D., Kojima, M., Oki, R., Nakamura, K., & Iguchi, T. (2014) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-13-00164.1 · Cited by 2,766
New, M., Hulme, M., & Jones, P. (1999) · Journal of Climate · doi:10.1175/1520-0442(1999)012<0829:rtcstc>2.0.co;2 · Cited by 1,795
Ashouri, H., Hsu, K.-L., Sorooshian, S., Braithwaite, D. K., Knapp, K. R., Cecil, L. D., Nelson, B. R., & Prat, O. P. (2015) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-13-00068.1 · Cited by 1,384
A Gauge-Based Analysis of Daily Precipitation over East Asia
Xie, P., Chen, M., Yang, S., Yatagai, A., Hayasaka, T., Fukushima, Y., & Liu, C. (2007) · Journal of Hydrometeorology · doi:10.1175/jhm583.1 · Cited by 1,138
Ebert, E. E., Janowiak, J. E., & Kidd, C. (2007) · Bulletin of the American Meteorological Society · doi:10.1175/bams-88-1-47 · Cited by 1,029
A 44-Year Daily Gridded Precipitation Dataset for Asia Based on a Dense Network of Rain Gauges
Yatagai, A., Arakawa, O., Kamiguchi, K., Kawamoto, H., Nodzu, M. I., & Hamada, A. (2009) · SOLA · doi:10.2151/sola.2009-035 · Cited by 554
Cited by
Validation of IMERG Precipitation in Africa
Dezfuli, A. K., Ichoku, C. M., Huffman, G. J., Mohr, K. I., Selker, J. S., van de Giesen, N., Hochreutener, R., & Annor, F. O. (2017) · Journal of Hydrometeorology · doi:10.1175/jhm-d-17-0139.1 · Cited by 162
Metadata
- Authors
- Sharifi, E., Steinacker, R., & Saghafian, B.
- Venue
- Remote Sensing
- Publisher
- MDPI AG
- Published
- 2016-02-06
- Volume
- 8
- Issue
- 2
- Pages
- 135
- ISSN
- 2072-4292 (ISSN-L)
- OpenAlex
- W2269631561
- Cited by
- 382
- References
- 19
- FWCI
- 20.33
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Assessment of GPM-IMERG and Other Precipitation Products against Gauge Data under Different Topographic and Climatic Conditions in Iran: Preliminary Results. https://app.cochat.ai/papers/10.3390/rs8020135
- The paper
- Sharifi, E., Steinacker, R., & Saghafian, B. (2016). Assessment of GPM-IMERG and Other Precipitation Products against Gauge Data under Different Topographic and Climatic Conditions in Iran: Preliminary Results. Remote Sensing. https://doi.org/10.3390/rs8020135
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.