Probabilistic precipitation estimation with a satellite product

Climate

Volumn 3, Issue 2, 2015, Pages 329-348

  Krakauer, Nir Y ^a   Pradhanang, Soni M ^b   Panthi, Jeeban ^c   Lakhankar, Tarendra ^a   Jha, Ajay K ^d  

^a City College of New York   (United States)

^b UNIVERSITY OF RHODE ISLAND   (United States)

^c The Small Earth Nepal (SEN)   (Nepal)

^d Veterinary Dentistry and Oral Surgery   (United States)

Author keywords

Generalized linear model; Himalayas; Monsoon asia; Nepal; Quantitative precipitation estimation

Indexed keywords

EID: 84971434202     PISSN: None     EISSN: 22251154     Source Type: Journal    
DOI: 10.3390/cli3020329     Document Type: Article

References (70)

1. Serrat-Capdevila, A.; Valdes, J.B.; Stakhiv, E.Z. Water management applications for satellite precipitation products: Synthesis and recommendations. J. Am. Water Resour. Assoc. 2014, 50, 509-525.
2. Chalise, S.B.; Shrestha, M.L.; Thapa, K.B.; Shrestha, B.R.; Bajracharya, B. Climate and Hydrological Atlas of Nepal; International Center for Integrated Mountain Development: Kathmandu, New Zealand, 1996.
3. Panthi, J.; Dahal, P.; Shrestha, M.L.; Aryal, S.; Krakauer, N.Y.; Pradhanang, S.M.; Lakhankar, T.; Jha, A.K.; Sharma, M.; Karki, R. Spatial and Temporal Variability of Rainfall in the Gandaki River Basin of Nepal Himalaya. Climate 2015, 3, 210-226.
4. Dhakal, C.K.; Regmi, P.P.; Dhakal, I.P.; Khanal, B.; Bhatta, U.K. Livelihood Vulnerability to Climate Change based on Agro Ecological Regions of Nepal. Glob. J. Sci. Front. Res. 2013, 13, 47-53.
5. Pradhanang, U.B.; Pradhanang, S.M.; Sthapit, A.; Krakauer, N.Y.; Jha, A.; Lakhankar, T. National livestock policy of Nepal: Needs and opportunities. Agriculture 2015, 5, 103-131.
6. Krakauer, N.Y.; Pradhanang, S.M.; Lakhankar, T.; Jha, A.K. Evaluating satellite products for precipitation estimation in mountain regions: A case study for Nepal. Remote Sens. 2013, 5, 4107-4123.
7. Hossain, F.; Huffman, G.J. Investigating error metrics for satellite rainfall data at hydrologically relevant scales. J. Hydrometeorol. 2008, 9, 563-575.
8. 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. The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J. Hydrometeorol. 2007, 8, 38-55.
9. Kummerow, C.; Barnes, W.; Kozu, T.; Shiue, J.; Simpson, J. The Tropical Rainfall Measuring Mission (TRMM) sensor package. J. Atmos. Ocean. Technol. 1998, 15, 809-817.
10. Huffman, G.; Adler, R.; Bolvin, D.; Nelkin, E. The TRMM multi-satellite precipitation analysis (TMPA). In Satellite Rainfall Applications For Surface Hydrology; Springer: Berlin, Germany, 2010; pp. 3-22.
11. Chen, S.; Hong, Y.; Cao, Q.; Gourley, J.J.; Kirstetter, P.E.; Yong, B.; Tian, Y.; Zhang, Z.; Shen, Y.; Hu, J.; Hardy, J. Similarity and difference of the two successive V6 and V7 TRMM multisatellite precipitation analysis performance over China. J. Geophys. Res. Atmosp. 2013, 118, 13060-13074
12. Qiao, L.; Hong, Y.; Chen, S.; Zou, C.B.; Gourley, J.J.; Yong, B. Performance assessment of successive Version 6 and Version 7 TMPA products over the climate-transitional zone in the southern Great Plains, USA. J. Hydrol. 2014, 513, 446-456.
13. Chen, S.; Hong, Y.; Gourley, J.J.; Huffman, G.J.; Tian, Y.; Cao, Q.; Yong, B.; Kirstetter, P.E.; Hu, J.; Hardy, J.; Li, Z.; Khan, S.I.; Xue, X. Evaluation of the successive V6 and V7 TRMM multisatellite precipitation analysis over the Continental United States. Water Resour. Res. 2013, 49, 8174-8186.
14. Gourley, J.J.; Hong, Y.; Flamig, Z.L.; Li, L.; Wang, J. Intercomparison of rainfall estimates from radar, satellite, gauge, and combinations for a season of record rainfall. J. Appl. Meteorol. Climatol. 2010, 49, 437-452.
15. Hirpa, F.A.; Gebremichael, M.; Hopson, T. Evaluation of high-resolution satellite precipitation products over very complex terrain in Ethiopia. J. Appl. Meteorol. Climatol. 2010, 49, 1044-1051.
16. Yong, B.; Chen, B.; Gourley, J.J.; Ren, L.; Hong, Y.; Chen, X.; Wang, W.; Chen, S.; Gong, L. Intercomparison of the Version-6 and Version-7 TMPA precipitation products over high and low latitudes basins with independent gauge networks: Is the newer version better in both real-time and post-real-time analysis for water resources and hydrologic extremes? J. Hydrol. 2014, 508, 77-87.
17. Moazami, S.; Golian, S.; Hong, Y.; Sheng, C.; Kavianpour, M.R. Comprehensive evaluation of four high-resolution satellite precipitation products over diverse climate conditions in Iran. Hydrol. Sci. J. 2014, doi: 10.1080/02626667.2014.987675.
18. Huang, Y.; Chen, S.; Cao, Q.; Hong, Y.; Wu, B.; Huang, M.; Qiao, L.; Zhang, Z.; Li, Z.; Li, W.a. Evaluation of version-7 TRMM multi-satellite precipitation analysis product during the Beijing extreme heavy rainfall event of 21 July 2012. Water 2014, 6, 32-44.
19. Liu, Z. Comparison of precipitation estimates between Version 7 3-hourly TRMM Multi-Satellite Precipitation Analysis (TMPA) near-real-time and research products. Atmos. Res. 2015, 153, 119-133.
20. Tong, K.; Su, F.; Yang, D.; Hao, Z. Evaluation of satellite precipitation retrievals and their potential utilities in hydrologic modeling over the Tibetan Plateau. J. Hydrol. 2014, 519A, 423-437.
21. Mantas, V.M.; Liu, Z.; Caro, C.; Pereira, A.J.S.C. Validation of TRMM multi-satellite precipitation analysis (TMPA) products in the Peruvian Andes. Atmos. Res. 2015, in press.
22. Yatagai, A.; Kamiguchi, K.; Arakawa, O.; Hamada, A.; Yasutomi, N.; Kitoh, A. APHRODITE: Constructing a long-term daily gridded precipitation dataset for Asia based on a dense network of rain gauges. Bull. Am. Meteorol. Soc. 2012, 93, 1401-1415.
23. Theis, S.E.; Hense, A.; Damrath, U. Probabilistic precipitation forecasts from a deterministic model: A pragmatic approach. Meteorol. Appl. 2005, 12, 257-268.
24. Hamill, T.M. Verification of TIGGE Multimodel and ECMWF Reforecast-Calibrated Probabilistic Precipitation Forecasts over the Contiguous United States. Mon. Weather Rev. 2012, 140, 2232-2252.
25. Mason, S.J.; Goddard, L. Probabilistic precipitation anomalies associated with ENSO. Bull. Am. Meteorol. Soc. 2001, 82, 619-638.
26. Barnston, A.G.; Mason, S.J. Evaluation of IRI's seasonal climate forecasts for the extreme 15% tails. Weather Forecast. 2011, 26, 545-554.
27. Krakauer, N.Y.; Grossberg, M.D.; Gladkova, I.; Aizenman, H. Information content of seasonal forecasts in a changing climate. Adv. Meteorol. 2013, 2013, 480210.
28. Luo, L.; Tang, W.; Lin, Z.; Wood, E.F. Evaluation of summer temperature and precipitation predictions from NCEP CFSv2 retrospective forecast over China. Clim. Dyn. 2013, 41, 2213-2230.
29. Germann, U.; Berenguer, M.; Sempere-Torres, D.; Zappa, M. REAL-Ensemble radar precipitation estimation for hydrology in a mountainous region. Q. J. R. Meteorol. Soc. 2009, 135, 445-456.
30. Tesfagiorgis, K.; Mahani, S.E.; Krakauer, N.Y.; Khanbilvardi, R. Bias correction of satellite rainfall estimates using a radar-gauge product -a case study in Oklahoma (USA). Hydrol. Earth Syst. Sci. 2011, 15, 2631-2647.
31. Schaake, J.; Demargne, J.; Hartman, R.; Mullusky, M.; Welles, E.; Wu, L.; Herr, H.; Fan, X.; Seo, D.J. Precipitation and temperature ensemble forecasts from single-value forecasts. Hydrol. Earth Syst. Sci. Discuss. 2007, 4, 655-717.
32. Bellerby, T.J.; Sun, J. Probabilistic and ensemble representations of the uncertainty in an IR/microwave satellite precipitation product. J. Hydrometeorol. 2005, 6, 1032-1044.
33. Gebremichael, M.; Liao, G.Y.; Yan, J. Nonparametric error model for a high resolution satellite rainfall product. Water Resour. Res. 2011, 47, W07504.
34. Dunn, P.K. Occurrence and quantity of precipitation can be modelled simultaneously. Int. J. Climatol. 2004, 24, 1231-1239.
35. Hasan, M.M.; Dunn, P.K. Two Tweedie distributions that are near-optimal for modelling monthly rainfall in Australia. Int. J. Climatol. 2011, 31, 1389-1397.
36. Chandler, R.E. On the use of generalized linear models for interpreting climate variability. Environmetrics 2005, 16, 699-715.
37. Krakauer, N.Y.; Devineni, N. Up-to-date probabilistic temperature climatologies. Environ. Res. Lett. 2015, 10, 024014.
38. Draper, N.R.; Smith, H. Applied Regression Analysis; Wiley: New York, NY, USA, 1966.
39. Eaton, J.W. GNU Octave and reproducible research. J. Process Control 2012, 22, 1433-1438.
40. Hurvich, C.M.; Simonoff, J.S.; Tsai, C.L. Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion. J. R. Stat. Soc. 1998, 60B, 271-293.
41. Krakauer, N.Y.; Krakauer, J.C. A new body shape index predicts mortality hazard independently of body mass index. PLoS ONE 2012, 7, e39504.
42. Stern, R.D. The calculation of probability distributions for models of daily precipitation. Arch. Meteorol. Geophys. Bioklimatol. Serie B 1980, 28, 137-147.
43. Groisman, P.Y.; Karl, T.R.; Easterling, D.R.; Knight, R.W.; Jamason, P.F.; Hennessy, K.J.; Suppiah, R.; Page, C.M.; Wibig, J.; Fortuniak, K.; Razuvaev, V.N.; Douglas, A.; FÃÿrland, E.; Zhai, P.M. Changes in the probability of heavy precipitation: important indicators of climatic change. Clim. Chang. 1999, 42, 243-283.
44. Semenov, V.; Bengtsson, L. Secular trends in daily precipitation characteristics: Greenhouse gas simulation with a coupled AOGCM. Clim. Dyn. 2002, 19, 123-140.
45. Wilson, P.S.; Toumi, R. A fundamental probability distribution for heavy rainfall. Geophys. Res. Lett. 2005, 32, 022465.
46. Li, C.; Singh, V.P.; Mishra, A.K. A bivariate mixed distribution with a heavy-tailed component and its application to single-site daily rainfall simulation. Water Resour. Res. 2013, 49, 767-789.
47. Feldmann, A.; Whitt, W. Fitting mixtures of exponentials to long-tail distributions to analyze network performance models. In Proceedings of the Sixteenth IEEE Annual Joint Conference of the Computer and Communications Societies, Kobe, Japan, 7-12 April 1997.
48. Wilks, D.S. Interannual variability and extreme-value characteristics of several stochastic daily precipitation models. Agric. For. Meteorol. 1999, 93, 153-169.
49. Shamir, E.; Wang, J.; Georgakakos, K.P. Probabilistic streamflow generation model for data sparse arid watersheds. J. Am. Water Resour. Assoc. 2007, 43, 1142-1154.
50. Shamir, E.; Megdal, S.B.; Carrillo, C.; Castro, C.L.; Chang, H.I.; Chief, K.; Corkhill, F.E.; Eden, S.; Georgakakos, K.P.; Nelson, K.M.; Prietto, J. Climate change and water resourcesmanagement in the Upper Santa Cruz River, Arizona. J. Hydrol. 2015, 521, 18-33.
51. Bogner, K.; Pappenberger, F.; Cloke, H.L. Technical Note: The normal quantile transformation and its application in a flood forecasting system,. Hydrol. Earth Syst. Sci. 2012, 16, 1085-1094.
52. Lin, C.J.;Weng, R.C.; Keerthi, S.S. Trust region Newton method for large-scale logistic regression. J. Mach. Learn. Res. 2008, 9, 627-650.
53. Fan, R.E.; Chang, K.W.; Hsieh, C.J.; Wang, X.R.; Lin, C.J. LIBLINEAR: A library for large linear classification. J. Mach. Learn. Res. 2008, 9, 1871-1874.
54. Roulston, M.S.; Smith, L.A. Evaluating probabilistic forecasts using information theory. Mon. Weather Rev. 2002, 130, 1653-1660.
55. Benedetti, R. Scoring rules for forecast verification. Mon. Weather Rev. 2010, 138, 203-211.
56. Shrestha, D.; Deshar, R. Diurnal variation of pre-monsoon and monsoon rainfall over Nepal. In Proceedings of the 2014 Seminar on Water & Energy, Kathmandu, Nepal, 24 March 2014.
57. Bhatt, B.C.; Nakamura, K. Characteristics of monsoon rainfall around the Himalayas revealed by TRMM precipitation radar. Mon. Weather Rev. 2005, 133, 149-165.
58. Bogardi, I.; Matyasovszky, I.; Bardossy, A.; Duckstein, L. Application of a space-time stochastic model for daily precipitation using atmospheric circulation patterns. J. Geophys. Res. 1993, 98, 16653-16667.
59. Morin, J.; Block, P.; Rajagopalan, B.; Clark, M. Identification of large scale climate patterns affecting snow variability in the eastern United States. Int. J. Climatol. 2007, 28, 315-328.
60. Kenyon, J.; Hegerl, G.C. Influence of modes of climate variability on global precipitation extremes. J. Clim. 2010, 23, 6248-6262.
61. Lang, T.J.; Barros, A.P. Winter storms in the central Himalayas. J. Meteorol. Soc. Jpn. 2004, 82, 829-844.
62. Anders, A.M.; Roe, G.H.; Hallet, B.; Montgomery, D.R.; Finnegan, N.J.; Putkonen, J. Spatial patterns of precipitation and topography in the Himalaya. Geol. Soc. Am. Special Papers 2006, 398, 39-53.
63. Mirakbari, M.; Ganji, A.; Fallah, S. Regional bivariate frequency analysis of meteorological droughts. J. Hydrol. Eng. 2010, 15, 985-1000.
64. Peleg, N.; Shamir, E.; Georgakakos, K.P.; Morin, E. A framework for assessing hydrological regime sensitivity to climate change in a convective rainfall environment: a case study of two medium-sized eastern Mediterranean catchments, Israel. Hydrol. Earth Syst. Sci. 2015, 19, 567-581.
65. Nelder, J.A.; Mead, R. A simplex method for function minimization. Comput. J. 1965, 7, 308-313.
66. Asmussen, S.; Nerman, O.; Olsson, M. Fitting phase-type distributions via the EM algorithm. Scan. J. Stat. 1996, 23, 419-441.
67. Horváth, A.; Telek, M. PhFit: A general phase-type fitting tool. In Computer Performance Evaluation: Modelling Techniques and Tools; Field, T., Harrison, P., Bradley, J., Harder, U., Eds.; Springer: Berlin, Germany, 2002; pp. 82-91.
68. Gleser, L.J. The gamma distribution as a mixture of exponential distributions. Am. Stat. 1989, 43, 115-117.
69. Botta, R.F.; Harris, C.M. Approximation with generalized hyperexponential distributions: Weak convergence results. Queueing Syst. 1986, 1, 169-190.
70. Riska, A.; Diev, V.; Smirni, E. An EM-based technique for approximating long-tailed data sets with PH distributions. Perform. Eval. 2004, 55, 147-164