Evaluation of a forward operator to assimilate cloud water path into WRF-DART

Monthly Weather Review

Volumn 141, Issue 7, 2013, Pages 2272-2289

  Jones, Thomas A ^a   Stensrud, David J ^b   Minnis, Patrick ^b   Palikonda, Rabindra ^c  

^a UNIVERSITY OF OKLAHOMA   (United States)

^b NATIONAL SEVERE STORMS LABORATORY   (United States)

^c NONE

Author keywords

[No Author keywords available]

Indexed keywords

ADVANCED RESEARCHES; DATA ASSIMILATION; ENSEMBLE KALMAN FILTER; LIMITED ATTENTIONS; ROOT MEAN SQUARES; SEVERE WEATHER EVENTS; SPATIAL ORIENTATIONS; WEATHER RESEARCH AND FORECASTING MODELS;

DATA PROCESSING; RESEARCH; SATELLITES;

WEATHER FORECASTING;

CLOUD WATER; DATA ASSIMILATION; ENSEMBLE FORECASTING; KALMAN FILTER; NUMERICAL MODEL; SEVERE WEATHER; WEATHER FORECASTING;

EID: 84880749700     PISSN: 00270644     EISSN: 15200493     Source Type: Journal    
DOI: 10.1175/MWR-D-12-00238.1     Document Type: Article

References (63)

1. Aksoy, A., D. Dowell, and C. Snyder, 2009: A multicase comparative assessment of the ensemble Kalman filter for assimilation of radar observations. Part I: Storm-scale analyses. Mon. Wea. Rev., 137, 1805-1824.
2. Anderson, J. L., T. Hoar, K. Raeder, H. Liu, N. Collins, R. Torn, and A. Avellano, 2009: The Data Assimilation Research Testbed: A community data assimilation facility. Bull. Amer. Meteor. Soc., 90, 1283-1296.
3. Benedetti, A., and M. Janiskova, 2008: Assimilation of MODIS cloud optical depths in the ECMWF model. Mon. Wea. Rev., 136, 1727-1746.
4. Brennan, J. I., Y. J. Kaufman, I. Koren, and R. R. Li, 2005: Aerosolcloud interaction-misclassification of MODIS clouds in heavy aerosol. IEEE Trans. Geosci. Remote Sens., 43, 911-915.
5. Caya, A., J. Sun, and C. Snyder, 2005: A comparison between the 4DVARand ensemble Kalman filter techniques for radar data assimilation. Mon. Wea. Rev., 133, 3081-3094.
6. Chang, F.-L., P. Minnis, B. Lin, M. Khaiyer, R. Palikonda, and D. Spangenberg, 2010a:Amodified method for inferring cloud top height using GOES 12 imager 10.7 and 13.3-mm data. J. Geophys. Res., 115, D06208, doi:10.1029/2009JD012304.
7. Chang, F.-L., P. Minnis, S. Sun-Mack, L. Nyugen, and Y. Chen, 2010b: On the satellite determination of multi-layered multi-phase cloud properties. Preprints, 13th Conf. on Cloud Physics/13th Conf. on Atmospheric Radiation, Portland, OR, Amer. Meteor. Soc., JP1.10. [Available online at https://ams.confex.com/ams/pdfpapers/171180.pdf.]
8. Chen, Y., F. Weng, Y. Han, and Q. Liu, 2008: Validation of the Community Radiative Transfer Model by using CloudSat data. J. Geophys. Res., 113, D00A03, doi:10.1029/2007JD009561.
9. Derber, J. C., and W.-S. Wu, 1998: The use of TOVS cloud-cleared radiances in the NCEP SSI analysis system. Mon. Wea. Rev., 126, 2287-2299.
10. Dong, X., P. Minnis, G. G. Mace, W. L. Smith Jr., M. Poellot, R. T. Marchand, and A. D. Rapp, 2002: Comparison of stratus cloud properties deduced from surface, GOES, and aircraft data during the March 2000 ARM Cloud IOP. J. Atmos. Sci., 59, 3256-3284.
11. Dong, X., P. Minnis, B. Xi, S. Sun-Mack, and Y. Chen, 2008: Comparison of CERES-MODIS stratus cloud properties with ground-based measurements at the DOE ARM Southern Great Plains site. J. Geophys. Res., 113, D03204, doi:10.1029/2007JD008438.
12. Dowell, D. C., G. S. Romine, and C. Snider, 2010: Ensemble stormscale data assimilation and prediction for severe convective storms. Preprints, 25th Conf. on Severe Local Storms, Denver, CO,Amer. Meteor. Soc., 9.5. [Available online at https://ams.confex.com/ams/pdfpapers/176121.pdf.]
13. Errico, R. M., 2000: The dynamical balance of leading singular vectors in a primitive-equation model. Quart. J. Roy. Meteor. Soc., 126, 1601-1618.
14. Errico, R. M., G. Ohring, F. Weng, P. Bauer, B. Ferrier, J.-F. Mahfouf, and J. Turk, 2007: Assimilation of satellite cloud and precipitation observations in numerical weather prediction models: Introduction to the JAS special collection. J. Atmos. Sci., 64, 3737-3741.
15. Gaspari, G., and S. E. Cohn, 1999: Construction of correlation functions in two and three dimensions. Quart. J. Roy. Meteor. Soc., 125, 723-757.
16. Heemink, A. W., M. Verlaan, and A. J. Segers, 2001: Variance reduced ensemble Kalman filtering. Mon. Wea. Rev., 129, 1718-1728.
17. Hong, S.-Y., and H.-L. Pan, 1996: Nonlocal boundary layer vertical diffusion in a medium-range forecast model. Mon. Wea. Rev., 124, 2322-2339.
18. Jones, T. A., and S. A. Christopher, 2010: Satellite and radar remote sensing of southern Plains grass fires: A case study. J. Appl. Meteor. Climatol., 49, 2133-2146.
19. Jones, T. A.,and D. J. Stensrud, 2012: Assimilating AIRS temperature and mixing ratio profiles using an ensemble Kalman filter approach for convective-scale forecasts. Wea. Forecasting, 27, 541-564.
20. Kalman, R. E., 1960: A new approach to linear filtering and prediction problems. J. Basic Eng., 82, 35-45.
21. Kato, S., L.M. Hinkelman, and A. Cheng, 2006: Estimate of satellitederived cloud optical thickness and effective radius errors and their effect on computed domain-averaged irradiances. J. Geophys. Res., 111, D17201, doi:10.1029/2005JD006668.
22. Lauwaet, D., K. D. Ridder, and P. Pandey, 2011: Assimilating remotely sensed cloud optical thickness into a mesoscale model. Atmos. Chem. Phys. Discuss., 11, 13355-13380.
23. Lin, Y., G. DiMego, B. Ferrier, J. Jung, D. Keyser, and E. Rodgers, 2003: Assimilation of GOES cloud top pressure data into the Eta Model. JSC/CAS Working Group on Numerical Experimentation (WGNE) Blue Book 2003, 2 pp. [Available online at http://www.wcrp-climate.org/WGNE/BlueBook/2003/individual-articles/01-lin.pdf.]
24. Mace, G. G., Y. Zhang, S. Platnick, M. D. King, P. Minnis, and P. Yang, 2005: Evaluation of cirrus cloud properties from MODIS radiances using cloud properties derived fromgroundbased data collected at theARMSGP site. J. Appl.Meteor., 44, 221-240.
25. Mansell, E. R., C. L. Ziegler, and E. C. Bruning, 2010: Simulated electrification of a small thunderstorm with two-moment bulk microphysics. J. Atmos. Sci., 67, 171-194.
26. McNally, A. P., J. C. Derber, W.-S. Wu, and B. B. Katz, 2000: The use of TOVS level-1B radiances in the NCEP SSI analysis system. Quart. J. Roy. Meteor. Soc., 126, 689-724.
27. McNally, A. P., P. D. Watts, J. A. Smith, R. Engelen, G. A. Kelly, J.-N. Thépaut, and M. Matricard, 2006: The assimilation of AIRS radiance data at ECMWF. Quart. J. Roy. Meteor. Soc., 132, 935-957.
28. McPherson, R. A., and Coauthors, 2007: Statewide monitoring of the mesoscale environment: A technical update on the Oklahoma Mesonet. J. Atmos. Oceanic Technol., 24, 301-321.
29. Mecikalski, J. R., P. Minnis, and R. Palikonda, 2013: Use of satellite derived cloud properties to quantify growing cumulus beneath cirrus clouds. Atmos. Res., 120-121, 192-201.
30. Menzel, W. P., and J. F. Purdom, 1994: Introducing GOES-I: The first of a new generation of geostationary operational environmental satellites. Bull. Amer. Meteor. Soc., 75, 757-781.
31. Migliorini, S., 2012: On the equivalence between radiance and retrieval assimilation. Mon. Wea. Rev., 140, 258-265.
32. Milbrandt, J. A., and M. K. Yau, 2005: A multimoment bulk microphysics parameterization. Part I: Analysis of the role of the spectral shape parameter. J. Atmos. Sci., 62, 3051-3064.
33. Minnis, P., J. Huang, B. Lin, Y. Yi, R. F. Arduini, T.-F. Fan, J. K. Ayers, and G. G. Mace, 2007: Ice cloud properties in ice-overwater cloud systems using Tropical Rainfall Measuring Mission (TRMM) visible and infrared scanner and TRMM Microwave Imager data. J. Geophys. Res., 112, D06206, doi:10.1029/ 2006JD007626.
34. Minnis, P., and Coauthors, 2008a: Near-real time cloud retrievals from operational and research meteorological satellites. Proc. SPIE Europe Remote Sens., 7107-2, Cardiff, Wales, SPIE, 1-8.
35. Minnis, P., and Coauthors, 2008b: Cloud detection in non-polar regions for CERES using TRMM VIRS and Terra and Aqua MODIS data. IEEE Trans. Geosci. Remote Sens., 46, 3857-3884.
36. Minnis, P., and Coauthors, 2010: CERES Edition 3 cloud retrievals. Preprints, 13th Conf. on Atmospheric Radiation, Portland, OR, Amer. Meteor. Soc., 5.4. [Available online at https://ams.confex.com/ams/pdfpapers/171366.pdf.]
37. Minnis, P., and Coauthors, 2011: CERES Edition-2 cloud property retrievals using TRMM VIRS and Terra and Aqua MODIS data. Part I: Algorithms. IEEE Trans. Geosci. Remote Sens., 49, 4374-4400.
38. Minnis, P., and Coauthors, 2012: Simulations of infrared radiances over a deep convective cloud system observed during TC4: Potential for enhancing nocturnal ice cloud retrievals. Remote Sens., 4, 3022-3054.
39. Otkin, J. A., 2010: Clear and cloudy sky infrared brightness temperature assimilation using an ensemble Kalman filter. J. Geophys. Res., 115, D19207, doi:10.1029/2009JD013759.
40. Painemal,D., P.Minnis, J. K.Ayers, and L. O'Neill, 2012: GOES- 10 microphysical retrievals in marine warm clouds: Multiinstrument validation and daytime cycle over the southeast Pacific. J. Geophys. Res., 117, D19212, doi:10.1029/2012JD017822.
41. Parrish, D. F., and J. C. Derber, 1992: The National Meteorological Center's spectral statistical interpolation analysis system. Mon. Wea. Rev., 120, 1747-1763.
42. Pavelin, E., S. English, and J. Eyre, 2008: The assimilation of cloudaffected infrared satellite radiances for numerical weather prediction. Quart. J. Roy. Meteor. Soc., 134, 737-749.
43. Pincus, R., R. J. P. Hofmann, J. L. Anderson, K. Raeder, N. Collins, and J. S. Whitaker, 2011: Can fully accounting for clouds in data assimilation improve short-term forecast by global models? Mon. Wea. Rev., 139, 946-956.
44. Polkinghorne, R., and T. Vukicevic, 2011: Data assimilation of cloud affected radiances in a cloud resolving model. Mon. Wea. Rev., 139, 755-773.
45. Polkinghorne, R., T. Vukicevic,and F. Evans, 2010: Validation of cloud resolving model background data for data assimilation. Mon. Wea. Rev., 138, 781-795.
46. Schmit, T. J., E. M. Prins, A. J. Schreiner, and J. J. Gurka, 2001: Introducing the GOES-M imager. Natl. Wea. Dig., 25, 28-37.
47. Schmit, T. J., M. M. Gunshor, W. P. Menzel, J. J. Gurka, J. Li, and A. S. Bachmeier, 2005: Introducing the next-generation Advanced Baseline Imager on GOES-R. Bull. Amer. Meteor. Soc., 86, 1079-1096.
48. Skamarock, W. C., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN-4751STR, 113 pp. [Available from UCAR Communications, P.O. Box 3000, Boulder, CO 80307.]
49. Smith, W. L., Jr., P. Minnis, L. Nguyen, D. Spangenberg, R. Austin, and G. Mace, 2007: Preliminary comparison of CloudSat liquid water path to passive satellite estimates. A-Train Symp., Lille, France, NASA. [Available online at http://www-angler.larc.nasa.gov/site/doc-library/52-Smith.Lille.07.pdf.]
50. Smith, W. L., Jr., P. Minnis, H. Finney, R. Palikonda, and M. M. Khaiyer, 2008: An evaluation of operational GOES-derived single-layer cloud top heights with ARSCL data over the ARM Southern Great Plains site. Geophys. Res. Lett., 35, L13820, doi:10.1029/ 2008GL034275.
51. Smith, W. L., Jr., P. Minnis, S. G. Benjamin, and S. S. Weygandt, 2010: 4-D water content fields derived from operational satellite data. Proc. IEEE 2010 Int. Geoscience and Remote Sensing Symp., Honolulu, HI, IEEE, 308-311.
52. Snyder, C., and F. Zhang, 2003: Assimilation of simulated Doppler radar observations with an ensemble Kalman filter. Mon. Wea. Rev., 131, 1663-1677.
53. Stein, T. H. M., J. Delan€oe, and R. J. Hogan, 2011: A comparison among four different methods for ice-cloud properties using data from CloudSat, CALIPSO, and MODIS. J. Appl. Meteor. Climatol., 50, 1952-1969.
54. Thompson, G., R. M. Rasmussen, and K. Manning, 2004: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and sensitivity analysis. Mon. Wea. Rev., 132, 519-542.
55. Tong, M., and M. Xue, 2005: Ensemble Kalman filter assimilation of Doppler radar data with compressible nonhydrostatic model: OSS experiments. Mon. Wea. Rev., 133, 1789-1807.
56. Torn, R. D., G. J. Hakim, and C. Snyder, 2006: Boundary conditions for limited area ensemble Kalman filters. Mon. Wea. Rev., 134, 2490-2502.
57. Vukicevic, T., T. Greenwald, M. Zupanski, D. Zupanski, T. Vonder Haar, and A. Jones, 2004: Mesoscale cloud state estimation from visible and infrared satellite radiances. Mon. Wea. Rev., 132, 3066-3077.
58. Vukicevic, T., M. Sengupta, A. Jones, and T. Vonder Haar, 2006: Cloud resolving data assimilation: Information content of IR window observations and uncertainties in estimation. J. Atmos. Sci., 63, 901-919.
59. Waliser, D., and Coauthors, 2009: Cloud ice: A climate model challenge with signs and expectations of progress. J. Geophys. Res., 114, D00A21, doi:10.1029/2008JD010015.
60. Weisz, E., J. Li, J. Li,D.K.Zhou, H.-L.Huang,M.D.Goldberg, and P. Yang, 2007: Cloudy sounding and cloud top height retrieval from AIRS alone single field-of-view radiance measurements. Geophys. Res. Lett., 34, L12802, doi:10.1029/2007GL030219.
61. Xue, M., M. Tong, and K. K. Droegemeier, 2006: An OSSE framework based on the ensemble square root Kalman filter for evaluating the impact of data from radar networks on thunderstorm analysis and forecasting. J. Atmos. Oceanic Technol., 23, 46-66.
62. Yucel, I., W. J. Shuttleworth, R. T. Pinker, L. Lu, and S. Sorooshian, 2002: Impact of ingesting satellite-derived cloud cover into the Regional Atmospheric Modeling System. Mon. Wea. Rev., 130, 610-628.
63. Yucel, I., W. J. Shuttleworth, X. Gao, and S. Sorooshian, 2003: Short-term performance of MM5 with cloud-cover assimilation from satellite observations. Mon. Wea. Rev., 131, 1797-1810.