Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 1,138

The DOI matches its Crossref record.

A Gauge-Based Analysis of Daily Precipitation over East Asia

Open access
Xie, Pingping, Chen, Mingyue, Yang, Song, Yatagai, Akiyo, Hayasaka, Tadahiro, Fukushima, Yoshihiro, Liu, Changming·2007·Journal of Hydrometeorology
DOI 10.1175/jhm583.1
Open this paper in CoChat — free account

Abstract

A new gauge-based analysis of daily precipitation has been constructed on a 0.5° latitude–longitude grid over East Asia (5°–60°N, 65°–155°E) for a 26-yr period from 1978 to 2003 using gauge observations at over 2200 stations collected from several individual sources. First, analyzed fields of daily climatology are computed by interpolating station climatology defined as the summation of the first six harmonics of the 365-calendar-day time series of the mean daily values averaged over a 20-yr period from 1978 to 1997. These fields of daily climatology are then adjusted by the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) monthly precipitation climatology to correct the bias caused by orographic effects. Gridded fields of the ratio of daily precipitation to the daily climatology are created by interpolating the corresponding station values using the optimal interpolation method. Analyses of total daily precipitation are finally calculated by multiplying the daily climatology by the daily ratio. Cross-validation tests indicated that this gauge-based analysis has high quantitative quality with a negligible bias and a correlation coefficient of ∼0.6 for comparisons between withdrawn station data and the analysis at a 0.05° latitude–longitude grid box. The quality of the analysis increases with the gauge network density. The mean distribution and annual cycle of this new gauge analysis present similar patterns but with more detailed structures and slightly larger magnitude compared to other published monthly gauge analyses over the region. The East Asia gauge analysis is applied to verify the performance of five satellite-based precipitation estimates. This examination reveals the regionally and seasonally dependent performance of the satellite products with the best statistics observed for relatively wet regions. Further improvements of the daily gauge analysis are underway to increase the gauge network density and to refine the algorithm to better deal with the orographic effects especially over South and Southeast Asia.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1175/jhm583.1

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.

A few free checks a day · papers already verified open instantly · results are public

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

No references could be resolved yet.

Research works printed but not linked: 69

  1. Adam, 2003, Adjustment of global gridded precipitation for systematic bias., J. Geophys. Res., 108, 10.1029/2002JD002499 · DOI · Paper page
  2. Adam, 2006, Correction of global precipitation products for orographic effects., J. Climate, 19, 15, 10.1175/JCLI3604.1 · DOI · Paper page
  3. Adler, 2001, Intercomparison of global precipitation products: The third Precipitation Intercomparison Project (PIP-3)., Bull. Amer. Meteor. Soc., 82, 1377, 10.1175/1520-0477(2001)082<1377:IOGPPT>2.3.CO;2 · doi:10.1175/1520-0477(2001)082<1377:iogppt>2.3.co;2
  4. Adler, 2003, The Version 2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present)., J. Hydrometeor., 4, 1147, 10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2 · DOI
  5. Arkin, 1987, The relationship between large-scale convective rainfall and cold cloud cover over the western hemisphere during 1982–1984., Mon. Wea. Rev., 115, 51, 10.1175/1520-0493(1987)115<0051:TRBLSC>2.0.CO;2 · doi:10.1175/1520-0493(1987)115<0051:trblsc>2.0.co;2
  6. Bradley, 1987, Precipitation fluctuations over Northern Hemisphere land areas since the mid-19th century., Science, 237, 171, 10.1126/science.237.4811.171 · DOI · Paper page
  7. Bussières, 1989, The objective analysis of daily rainfall by distance weighting schemes on a mesoscale grid., Atmos.–Ocean, 27, 521, 10.1080/07055900.1989.9649350 · DOI
  8. Chen, 2002, Global land precipitation: A 50-year monthly analysis based on gauge observations., J. Hydrometeor., 3, 249, 10.1175/1525-7541(2002)003<0249:GLPAYM>2.0.CO;2 · DOI · Paper page
  9. Chen, M., P.Xie, J. E.Janowiak, and P. A.Arkin, 2004: Orographic enhancements in precipitation: An intercomparison of two gauge-based precipitation climatologies. Preprints, 18th Conf. on Hydrology, Seattle, WA, Amer. Meteor. Soc., CD-ROM, 5.1.
  10. Creutin, 1982, Objective analysis and mapping techniques for rainfall fields: An objective comparison., Water Resour. Res., 18, 413, 10.1029/WR018i002p00413 · DOI · Paper page
  11. Dai, 2000, Global patterns of ENSO-induced precipitation., Geophys. Res. Lett., 27, 1283, 10.1029/1999GL011140 · DOI · Paper page
  12. Dai, 1997, Surface observed global land precipitation variations during 1900–88., J. Climate, 10, 2943, 10.1175/1520-0442(1997)010<2943:SOGLPV>2.0.CO;2 · doi:10.1175/1520-0442(1997)010<2943:soglpv>2.0.co;2
  13. Daly, 1994, A statistical-topographic model for mapping climatological precipitation over mountainous terrain., J. Appl. Meteor., 33, 140, 10.1175/1520-0450(1994)033<0140:ASTMFM>2.0.CO;2 · DOI · Paper page
  14. Daly, 2002, A knowledge-based approach to the statistical mapping of climate., Climate Res., 22, 99, 10.3354/cr022099 · DOI · Paper page
  15. Ebert, 1998, Performance of satellite rainfall estimation algorithms during TOGA COARE., J. Atmos. Sci., 55, 1537, 10.1175/1520-0469(1998)055<1537:POSREA>2.0.CO;2 · doi:10.1175/1520-0469(1998)055<1537:posrea>2.0.co;2
  16. Ebert, 2007, Comparison of near-real-time precipitation estimates from satellite observations and numerical models., Bull. Amer. Meteor. Soc., 88, 10.1175/BAMS-88-1-47 · DOI · Paper page
  17. Eischeid, J. K., H. F.Diaz, R. S.Bradley, and P. D.Jones, 1991: A comprehensive precipitation dataset for global land areas. U.S. Department of Energy Tech. Rep. DOE/ER-6901T-H1, 81 pp. [Available from National Technical Information Services, U.S. Department of Commerce, Springfield, VA 22161.]. · doi:10.2172/5967423
  18. Fekete, 2004, Uncertainties in precipitation and their impacts on runoff estimates., J. Climate, 17, 294, 10.1175/1520-0442(2004)017<0294:UIPATI>2.0.CO;2 · DOI · Paper page
  19. Ferraro, 1997, Special sensor microwave imager derived global rainfall estimates for climatological applications., J. Geophys. Res., 102, 16715, 10.1029/97JD01210 · doi:10.1029/97jd01210
  20. Frei, 1998, A precipitation climatology of the Alps from high-resolution rain-gauge observations., Int. J. Climatol., 18, 873, 10.1002/(SICI)1097-0088(19980630)18:8<873::AID-JOC255>3.0.CO;2-9 · DOI · Paper page
  21. Hsu, 1997, Precipitation estimation from remotely sensed information using artificial neural networks., J. Appl. Meteor., 36, 1176, 10.1175/1520-0450(1997)036<1176:PEFRSI>2.0.CO;2 · DOI · Paper page
  22. Huffman, 1997, The Global Precipitation Climatology Project (GPCP) combined precipitation dataset., Bull. Amer. Meteor. Soc., 78, 5, 10.1175/1520-0477(1997)078<0005:TGPCPG>2.0.CO;2 · DOI · Paper page
  23. Huffman, 2001, Global precipitation at one-degree daily resolution from multisatellite observations., J. Hydrometeor., 2, 36, 10.1175/1525-7541(2001)002<0036:GPAODD>2.0.CO;2 · DOI · Paper page
  24. Huffman, G. J., R. F.Adler, E. F.Stocker, D. T.Bolvin, and E. J.Nelkin, 2004: Analysis of TRMM 3-hourly multi-satellite precipitation estimates computed in both real and post-real time. Preprints, 12th Conf. on Satellite Meteorology and Oceanography, Long Beach, CA, Amer. Meteor. Soc., CD-ROM, P4.11.
  25. Huffman, 2007, The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales., J. Hydrometeor., 8, 38, 10.1175/JHM560.1 · DOI · Paper page
  26. Hulme, 1991, An intercomparison of model and observed global precipitation climatologies., Geophys. Res. Lett., 18, 1715, 10.1029/91GL01850 · DOI
  27. Hulme, 1997, Dependence of large-scale precipitation climatologies on temporal and spatial sampling., J. Climate, 10, 1099, 10.1175/1520-0442(1997)010<1099:DOLSPC>2.0.CO;2 · doi:10.1175/1520-0442(1997)010<1099:dolspc>2.0.co;2
  28. Janowiak, 1999, CAMS–OPI: A global satellite–rain gauge merged product for real-time precipitation monitoring applications., J. Climate, 12, 3335, 10.1175/1520-0442(1999)012<3335:COAGSR>2.0.CO;2 · DOI
  29. Janowiak, 2003, A global-scale examination of monsoon-related precipitation., J. Climate, 16, 4121, 10.1175/1520-0442(2003)016<4121:AGEOMP>2.0.CO;2 · doi:10.1175/1520-0442(2003)016<4121:ageomp>2.0.co;2
  30. Janowiak, 1998, A comparison of the NCEP–NCAR reanalysis precipitation and the GPCP rain gauge–satellite combined dataset with observational error considerations., J. Climate, 11, 2960, 10.1175/1520-0442(1998)011<2960:ACOTNN>2.0.CO;2 · DOI · Paper page
  31. Joyce, 2004, CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution., J. Hydrometeor., 5, 487, 10.1175/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2 · DOI · Paper page
  32. Kummerow, 2000, The status of the Tropical Rainfall Measuring Mission (TRMM) after two years in orbit., J. Appl. Meteor., 39, 1965, 10.1175/1520-0450(2001)040<1965:TSOTTR>2.0.CO;2 · DOI · Paper page
  33. Lau, 2001, Principal modes of rainfall–SST variability of the Asian summer monsoon: A reassessment of the monsoon–ENSO relationship., J. Climate, 14, 2880, 10.1175/1520-0442(2001)014<2880:PMORSV>2.0.CO;2 · DOI
  34. Legates, 1990, Mean seasonal and spatial variability in gauge-corrected, global precipitation., Int. J. Climatol., 10, 111, 10.1002/joc.3370100202 · DOI · Paper page
  35. Liu, 2004, Changes in components of the hydrological cycle in the Yellow River basin during the second half of the 20th century., Hydrol. Process., 18, 2337, 10.1002/hyp.5534 · doi:10.1002/hyp.5534
  36. McCollum, 2002, Evaluation of biases of satellite rainfall estimation algorithms over the continental United States., J. Appl. Meteor., 41, 1065, 10.1175/1520-0450(2002)041<1065:EOBOSR>2.0.CO;2 · doi:10.1175/1520-0450(2002)041<1065:eobosr>2.0.co;2
  37. Morrissey, 1995, The Pacific rain gauge rainfall database., Water Resour. Res., 31, 2111, 10.1029/95WR01233 · doi:10.1029/95wr01233
  38. Morrissey, 1995, The uncertainty of simple averages using rain gauge networks., Water Resour. Res., 31, 2011, 10.1029/95WR01232 · doi:10.1029/95wr01232
  39. New, 1999, Representing twentieth-century space–time climate variability. Part I: Development of a 1961–90 mean monthly terrestrial climatology., J. Climate, 12, 829, 10.1175/1520-0442(1999)012<0829:RTCSTC>2.0.CO;2 · DOI · Paper page
  40. New, 2000, Representing twentieth-century space–time climate variability. Part II: Development of 1901––96 monthly grids of terrestrial surface climate., J. Climate, 13, 2217, 10.1175/1520-0442(2000)013<2217:RTCSTC>2.0.CO;2 · DOI · Paper page
  41. Nijssen, 2001, Predicting the discharge of global rivers., J. Climate, 14, 3307, 10.1175/1520-0442(2001)014<3307:PTDOGR>2.0.CO;2 · DOI · Paper page
  42. Roads, 2001, ECPC’s weekly to seasonal global forecasts., Bull. Amer. Meteor. Soc., 82, 639, 10.1175/1520-0477(2001)082<0639:EWTSGF>2.3.CO;2 · doi:10.1175/1520-0477(2001)082<0639:ewtsgf>2.3.co;2
  43. Ropelewski, 1985, The analysis and display of real-time surface climate data., Mon. Wea. Rev., 113, 1101, 10.1175/1520-0493(1985)113<1101:TAADOR>2.0.CO;2 · doi:10.1175/1520-0493(1985)113<1101:taador>2.0.co;2
  44. Rubel, 2001, BALTEX 1/6-degree daily precipitation climatology 1996–1998., Meteor. Atmos. Phys., 77, 155, 10.1007/s007030170024 · doi:10.1007/s007030170024
  45. Rudolf, B. , 1993: Management and analysis of precipitation data on a routine basis. Proc. Int. Symp. on Precipitation and Evaporation. Bratislava, Slovakia, WMO, 69–76.
  46. Schaake, J., A.Henkel, and S.Cong, 2004: Application of PRISM climatologies for hydrologic modeling and forecasting in the western U.S. Preprints, 18th Conf. on Hydrology, Seattle, WA, Amer. Meteor. Soc., CD-ROM, 5.3.
  47. Schneider, U. , 1993: The GPCC quality-control system for gauge-measured precipitation data. Proc. Analysis Methods for Precipitation on a Global Scale: Report of a GEWEX Workshop, WCRP-81, WMO/TD-588, Koblenz, Germany, GPCC, A5–A9.
  48. Shepard, D. , 1968: A two dimensional interpolation function for irregularly spaced data. Proc. 23d National Conf. of the Association for Computing Machinery, Princeton, NJ, ACM, 517–524. · DOI · Paper page
  49. Sorooshian, 2000, Evaluation of PERSIANN system satellite-based estimates of tropical rainfall., Bull. Amer. Meteor. Soc., 81, 2035, 10.1175/1520-0477(2000)081<2035:EOPSSE>2.3.CO;2 · DOI · Paper page
  50. Spencer, 1993, Global oceanic precipitation from MSU during 1979–91 and comparisons to other climatologies., J. Climate, 6, 1301, 10.1175/1520-0442(1993)006<1301:GOPFTM>2.0.CO;2 · DOI · Paper page
  51. Su, 2005, Streamflow simulation of the terrestrial Arctic domain., J. Geophys. Res., 110, 10.1029/2004JD005518 · doi:10.1029/2004jd005518
  52. Susskind, 1997, Characteristics of the TOVS Pathfinder Path A dataset., Bull. Amer. Meteor. Soc., 78, 1449, 10.1175/1520-0477(1997)078<1449:COTTPP>2.0.CO;2 · doi:10.1175/1520-0477(1997)078<1449:cottpp>2.0.co;2
  53. Trenberth, 2000, The Southern Oscillation revisited: Sea level pressures, surface temperatures, and precipitation., J. Climate, 13, 4358, 10.1175/1520-0442(2000)013<4358:TSORSL>2.0.CO;2 · DOI · Paper page
  54. Turk, F. J., and P.Bauer, Eds.2005: Second International Precipitation Working Group Workshop. EUMETSAT Publication EUM P.44, 355 pp. [Available from EUMETSAT, Am Kavallerisesand 31, D-64295 Darmstadt, Germany.].
  55. Turk, 2005, Toward improved characterization of remotely sensed precipitation regimes with MODIS/AMSR-E blended data technique., IEEE Trans. Geosci. Remote Sens., 43, 1059, 10.1109/TGRS.2004.841627 · doi:10.1109/tgrs.2004.841627
  56. Turk, F. J., E. E.Ebert, B-J.Sohn, H-J.Oh, V.Levizzani, E. A.Smith, and R.Ferraro, 2004: Validation of an operational global precipitation analysis at short time scales. Preprints, 12th Conf. on Satellite Meteorology and Oceanography, Long Beach, CA, Amer. Meteor. Soc., CD-ROM, J1.2.
  57. Turk, F. J., P.Bauer, E.Ebert, and P. A.Arkin, 2006: Satellite-derived precipitation verification activities within the International Precipitation Working Group (IPWG). 14th Conf. on Satellite Meteorology and Oceanography, Atlanta, GA, Amer. Meteor. Soc., CD-ROM, P2.15.
  58. Vose, R. S., R. L.Schmoyer, P. M.Steurer, T. C.Peterson, R.Heim, T. R.Karl, and J. K.Eischeid, 1992: The Global Historical Climatology Network: Long-term monthly temperature, precipitation, sea-level pressure, and station pressure data. Tech. Rep. ORNL/CDIAC-53, Oak Ridge National Laboratory/Carbon Dioxide Information Analysis Center, Oak Ridge, TN, 26 pp. · DOI
  59. Weymouth, 1999, A continental-scale daily rainfall analysis system., Aust. Meteor. Mag., 48, 169
  60. Wilheit, 1991, Retrieval of monthly rainfall indices from microwave radiometric measurements using probability distribution functions., J. Atmos. Oceanic Technol., 8, 118, 10.1175/1520-0426(1991)008<0118:ROMRIF>2.0.CO;2 · doi:10.1175/1520-0426(1991)008<0118:romrif>2.0.co;2
  61. Willmott, 1995, Smart interpolation of annually averaged air temperature in the United States., J. Appl. Meteor., 34, 2577, 10.1175/1520-0450(1995)034<2577:SIOAAA>2.0.CO;2 · DOI · Paper page
  62. Willmott, 1996, Comparison of approaches for estimating time-averaged precipitation using data from the USA., Int. J. Climatol., 16, 1103, 10.1002/(SICI)1097-0088(199610)16:10<1103::AID-JOC78>3.0.CO;2-P · doi:10.1002/(sici)1097-0088(199610)16:10<1103::aid-joc78>3.0.co;2-p
  63. Xie, 1997, Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs., Bull. Amer. Meteor. Soc., 78, 2539, 10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2 · DOI · Paper page
  64. Xie, 1998, Global monthly precipitation estimates from satellite-observed outgoing longwave radiation., J. Climate, 11, 137, 10.1175/1520-0442(1998)011<0137:GMPEFS>2.0.CO;2 · DOI · Paper page
  65. Xie, 1996, Gauge-based monthly analysis of global land precipitation from 1971 to 1994., J. Geophys. Res., 101, 19023, 10.1029/96JD01553 · doi:10.1029/96jd01553
  66. Xie, 2003, GPCP pentad precipitation analyses: An experimental dataset based on gauge observations and satellite estimates., J. Climate, 16, 2197, 10.1175/2769.1 · DOI · Paper page
  67. Xue, 2005, Multiscale variability of the river runoff system in China and its long-term link to precipitation and sea surface temperature., J. Hydrometeor., 6, 550, 10.1175/JHM439.1 · doi:10.1175/jhm439.1
  68. Yatagai, 2005, Utilization of a new gauge-based daily precipitation dataset over monsoon Asia for validation of the daily precipitation climatology simulated by the MRI/JMA 20-km-mesh AGCM., Sci. Online Lett. Atmos., 1, 193
  69. Ye, 2004, A bias-corrected precipitation climatology for China., J. Hydrometeor., 5, 1147, 10.1175/JHM-366.1 · doi:10.1175/jhm-366.1

Cited by

See all 1,138

Metadata

Authors
Xie, P., Chen, M., Yang, S., Yatagai, A., Hayasaka, T., Fukushima, Y., & Liu, C.
Venue
Journal of Hydrometeorology
Publisher
American Meteorological Society
Published
2007-06-01
Volume
8
Issue
3
Pages
607-626
ISSN
  • 1525-7541 (ISSN-L)
  • 1525-755X
DOI
10.1175/jhm583.1
OpenAlex
W2143357393
Cited by
1,138
References
0
FWCI
12.66
Type
journal article
Language
en
Open access
bronze

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: A Gauge-Based Analysis of Daily Precipitation over East Asia. https://app.cochat.ai/papers/10.1175/jhm583.1
The paper
Xie, P., Chen, M., Yang, S., Yatagai, A., Hayasaka, T., Fukushima, Y., & Liu, C. (2007). A Gauge-Based Analysis of Daily Precipitation over East Asia. Journal of Hydrometeorology. https://doi.org/10.1175/jhm583.1

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.