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Reanalysis of the Indian summer monsoon: four dimensional data assimilation of AIRS retrievals in a regional data assimilation and modeling framework

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Abstract

This work is the first attempt to produce a multi-year downscaled regional reanalysis of the Indian summer monsoon (ISM) using the National Centers for Environmental Prediction (NCEP) operational analyses and Atmospheric Infrared Sounder (AIRS) version 5 temperature and moisture retrievals in a regional model. Reanalysis of nine monsoon seasons (2003–2011) are produced in two parallel setups. The first set of experiments simply downscale the original NCEP operational analyses, whilst the second one assimilates the AIRS temperature and moisture profiles. The results show better representation of the key monsoon features such as low level jet, tropical easterly jet, subtropical westerly jet, monsoon trough and the spatial pattern of precipitation when AIRS profiles are assimilated (compared to those without AIRS data assimilation). The distribution of temperature, moisture and meridional gradients of dynamical and thermodynamical fields over the monsoon region are better represented in the reanalysis that assimilates AIRS profiles. The change induced by AIRS data on the moist and thermodynamic conditions results in more realistic rendering of the vertical shear associated with the monsoon, which in turn leads to a proper moisture transport and the moist convective feedback. This feedback benefits the representation of the regional monsoon characteristics, the monsoon dynamics and the moist convective processes on the seasonal time scale. This study emphasizes the use of AIRS soundings for downscaling of ISM representation in a regional reanalysis.

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References

  • Abhik S, Mukhopadhyay P, Goswami B (2014) Evaluation of mean and intraseasonal variability of Indian summer monsoon simulation in ECHAM5: identification of possible source of bias. Clim Dyn 43:389–406

    Article  Google Scholar 

  • Anthes RA, Kuo YH, Hsie EY, Low-Nam S, Bettge TW (1989) Estimation of skill and uncertainty in regional numerical models. Q J R Meteorol Soc 115:763–806

    Article  Google Scholar 

  • Aumann HH, Chahine MT, Gautier C, Goldberg MD, Kalnay E, McMillin LM, Revercomb H, Rosenkranz PW, Smith WL, Staelin DH, Strow LL, Suskind J (2003) AIRS/AMSU/HSB on the Aqua mission: design, science objectives, data products, and processing system. IEEE Trans Geosci Remote Sens 41:253–264

    Article  Google Scholar 

  • Colle BA, Westrick KJ, Mass CF (1999) Evaluation of MM5 and Eta-10 precipitation forecast over the Pacific northwest during the cool season. Weather Forecast 14:137–154

    Article  Google Scholar 

  • Cressman GP (1959) An operational objective analysis system. Mon Wea Rev 87:367–374

    Article  Google Scholar 

  • Davolio S, Buzzi A (2004) A Nudging scheme for the assimilation of precipitation data into a mesoscale model. Weather Forecast 19:855–871

    Article  Google Scholar 

  • Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597

    Article  Google Scholar 

  • Divakarla MG, Barnet CD, Goldberg MD, McMillin LM, Maddy E, Wolf W, Zhou L, Liu X (2006) Validation of Atmospheric Infrared Sounder temperature and water vapor retrievals with matched radiosonde measurements and forecasts. J Geophys Res. doi:10.1029/2005JD006116

    Google Scholar 

  • Emanuel KA, Neelin JD, Bretherton CS (1994) On large-scale circulations in convective atmospheres. Q J R Meteorol Soc 120:1111–1143

    Article  Google Scholar 

  • Fan X, Tilley SJ (2005) Dynamic assimilation of MODIS-retrieved humidity profiles within a regional model for high-latitude forecast applications. Mon Weather Rev 133:3450–3480

    Article  Google Scholar 

  • Fast JD (1995) Mesoscale modeling and four-dimensional data assimilation in areas of highly complex terrain. J Appl Meteorol 34:2762–2782

    Article  Google Scholar 

  • Fu XH, Wang B, Tao L (2006) Satellite data reveal the 3-D moisture structure of tropical intraseasonal oscillation and its coupling with underlying ocean. Geophys Res Lett 33:L03705. doi:10.1029/2005GL025074

    Google Scholar 

  • Gadgil S, Gadgil S (2006) The Indian monsoon, GDP and agriculture. Econ Polit Wkly 41:4887–4895

    Google Scholar 

  • Huffman GJ, Adler RF, Morrissey M, Bolvin DT, Curtis S, Joyce R, McGavock B, Susskind J (2001) Global precipitation at one-degree daily resolution from multi-satellite observations. J Hydrometeorol 2:36–50. doi:10.1175/1525-7541(2001)002\0036:GPAODD

    Article  Google Scholar 

  • Huffman GJ, Adler RF, Bolvin DT, Gu G, Nelkin EJ, Bowman KP, Hong Y, Stocker EF, Wolff DB (2007) The TRMM multisatellite precipitation analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J Hydrometeorol 8:38–55

    Article  Google Scholar 

  • Jiang X, Li T, Wang B (2004) Structures and mechanisms of the northward propagating boreal summer intraseasonal oscillation. J Clim 17:1022–1039

    Article  Google Scholar 

  • Joseph PV, Sijikumar S (2004) Intraseasonal variability of the low-level jet stream of the Asian summer monsoon. J Clim 17:1449–1458

    Article  Google Scholar 

  • Krishnamurti TN, Bhalme HN (1976a) Oscillations of a monsoon system, part I: observational aspects. J Atmos Sci 33:1937–1954

    Article  Google Scholar 

  • Krishnamurti TN, Molinari J, Pan HL (1976b) Numerical simulation of the Somali jet. J Atmos Sci 33:2350–2362

    Article  Google Scholar 

  • Krishnamurti TN, Cunningham P, Rajendran K (2005) Anomalous gradient winds in the subtropical jet stream and interpretations of forecast failures. Meteorol Atmos Phys 88:237–250. doi:10.1007/s00703-004-0075-x

    Article  Google Scholar 

  • Lakshmivarahan S, Lewis JM (2011) When is nudging optimal. Technical report, School of Computer Science, University of Oklahoma, Norman, 73019

  • Lau K-M, Kim K-M, Yang S (2000) Dynamical and boundary forcing characteristics of regional components of the Asian summer monsoon. J Clim 13:2461–2482

    Article  Google Scholar 

  • Le Marshall J et al (2006) Improving global analysis and forecasting with AIRS. Bull Am Meteorol Soc 87:891–894

    Article  Google Scholar 

  • Leslie LM, LeMarshall JF, Morrison RP, Spinoso C, Purser RJ, Pescod N, Seecamp R (1998) Improved hurricane track forecasting from the continuous assimilation of high quality satellite wind data. Mon Weather Rev 126:1248–1257

    Article  Google Scholar 

  • Li J, Liu H (2009) Improved hurricane track and intensity forecast using single field-of-view advanced IR sounding measurements. Geophys Res Lett 36:L11813. doi:10.1029/2009GL038285

    Article  Google Scholar 

  • Liang X-Z, Xu M, Yuan X, Ling T, Choi HI, Zhang F, Chen L, Liu S, Su S, Qiao F, He Y, Wang JXL, Kunkel KE, Gao W, Joseph E, Morris V, Yu T-W, Dudhia J, Michalakes J (2012) Regional climate-weather research and forecasting model (CWRF). Bull Am Meteorol Soc. doi:10.1175/BAMS-D-11-00180.1

    Google Scholar 

  • Lin R, Zhou T, Qian Y (2014) Evaluation of global monsoon precipitation changes based on five reanalysis datasets. J Clim 27(3):1271–1289

    Article  Google Scholar 

  • Lucas-Picher P, Christensen JH, Saeed F, Kumar P, Asharaf S, Ahrens B, Wiltshire AJ, Jacob D, Hagemann S (2011) Can regional climate models represent the Indian monsoon? J Hydrometeorol 12(5):849–868. doi:10.1175/2011jhm1327.1

    Article  Google Scholar 

  • McNally AP, Watts PD (2003) A cloud detection algorithm for high-spectral-resolution infrared sounders. Q J R Meteorol Soc 129:3411–3423. doi:10.1256/qj.02.208

    Article  Google Scholar 

  • Miyoshi T, Kunii M (2012) Using AIRS retrievals in the WRF-LETKF system to improve regional numerical weather prediction. Tellus A 64:18408. doi:10.3402/tellusa.v64i0.18408

    Article  Google Scholar 

  • Otkin JA (2012) Assimilation of water vapor sensitive infrared brightness temperature observations during a high impact weather event. J Geophys Res 117:D19203. doi:10.1029/2012JD017568

    Article  Google Scholar 

  • Parkinson CL (2003) Aqua: an Earth-observing satellite mission to examine water and other climate variables. IEEE Trans Geosci Remote Sens 41:173–183

    Article  Google Scholar 

  • Raju A, Parekh A, Chowdary JS, Gnanaseelan C (2014) Impact of satellite retrieved atmospheric temperature profiles assimilation on Asian summer monsoon simulation. Theor Appl Climatol 116:317–326

    Article  Google Scholar 

  • Raju A, Parekh A, Chowdary JS, Gnanaseelan C (2015a) Assessment of the Indian summer monsoon in the WRF regional climate model. Clim Dyn 44:3077–3100. doi:10.1007/s00382-014-2295-1

    Article  Google Scholar 

  • Raju A, Parekh A, Kumar P, Gnanaseelan C (2015b) Evaluation of the impact of AIRS profiles on prediction of Indian summer monsoon using WRF variational data assimilation system. J Geophys Res Atmos 120:8112–8131. doi:10.1002/2014JD023024

    Article  Google Scholar 

  • Raju A, Parekh A, Sreenivas P, Chowdary JS, and Gnanaseelan C (2015c) Estimation of improvement in Indian summer monsoon circulation by assimilation of temperature profiles in WRF model. IEEE J Sel Top Appl Earth Obs Remote Sens. doi:10.1109/JSTARS.2015.2410338

    Google Scholar 

  • Rakesh V, Singh R, Joshi PC (2010) Impact of four dimensional assimilation of satellite data on long-range simulations over the Indian region during monsoon 2010. Adv Space Res 46:895–908

    Article  Google Scholar 

  • Raymond WH, Wade GS, Zapotocny TH (2004) Assimilating GOES brightness temperatures. Part I: upper-tropospheric moisture. J Appl Meteorol 43:17–27

    Article  Google Scholar 

  • Reale O, Lau KM, Susskind J, Rosenberg R (2012) AIRS impact on analysis and forecast of an extreme rainfall event (Indus River Valley, Pakistan, 2010) with a global data assimilation and forecast system. J Geophys Res 117:D08103. doi:10.1029/2011JD017093

    Article  Google Scholar 

  • Reale O, Achuthavarier D, Fuentes M, Putman W, Partyka G (2017) Tropical cyclone in the 7-km NASA nature run for use in observing system simulation experiments. J Atmos Oceanic Technol 34:73–100. doi:10.1175/JTECH-D-16-0094.1

    Article  Google Scholar 

  • Sabin TP, Krishnan R, Ghattas J, Denvil S, Dufresne J-F, Hourdin F, Pascal T (2013) High resolution simulation of the South Asian monsoon using a variable resolution global climate model. Clim Dyn 41:173–194

    Article  Google Scholar 

  • Seaman NL, Stauffer DR, Lario-Gibbs AM (1995) Amultiscale four-dimensional data assimilation system applied in the San Joaquin Valley during SARMAP. Part I: modeling design and basic performance characteristics. J Appl Meteorol 34:1739–1761

    Article  Google Scholar 

  • Singh R, Pal PK, Kishtawal CM, Joshi PC (2008) Impact of Atmospheric Infrared Sounder data on the numerical simulation of a historical Mumbai rain event. Weather Forecast 23:892–913

    Google Scholar 

  • Singh R, Pal PK, Joshi PC (2010) Assimilation of Kalpana very high resolution radiometer water vapor channel radiances into a mesoscale model. J Geophys Res 115:D18124. doi:10.1029/2010JD014027

    Article  Google Scholar 

  • Singh R, Kishtawal CM, Ojha SP, Pal PK (2012) Impact of assimilation of Atmospheric InfraRed Sounder (AIRS) radiances and retrievals in the WRF 3D-Var assimilation system. J Geophys Res 117:D11107. doi:10.1029/2011JD017367

    Google Scholar 

  • Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Duda MG, Huang XY, Wang W, Powers JG (2008) A description of the Advanced Research WRF Version 3. NCAR/TN-475 STR; NCAR Technical Note, Mesoscale and Microscale Meteorology Division, National Center of Atmospheric Research, pp. 113

  • Stauffer DR, Seaman NL (1990) Use of four-dimensional data assimilation in a limited-area mesoscale model. Part I: experiments with synoptic-scale data. Mon Weather Rev 118:1250–1277

    Article  Google Scholar 

  • Stauffer DR, Seaman NL (1994) Multiscale four-dimensional data assimilation. J Appl Meteorol 33:416–434

    Article  Google Scholar 

  • Stauffer DR, Seaman NL, Binkowski FS (1991) Use of four dimensional data assimilation in a limited area mesoscale model. Part II: effects of data assimilation within the planetary boundary layer. Mon Weather Rev 119:734–754

    Article  Google Scholar 

  • Susskind J, Reale O (2009) Improving forecast skill by assimilation of quality controlled AIRS Version 5 temperature soundings.In: Proc SPIE int symp infrared spaceborne remote sensing instrum XVII, vol 743. San Diego, p 74350G

  • Susskind J, Barnet C, Blaisdell J (2003) Retrieval of atmospheric and surface parameters from AIRS/ AMSU/HSB under cloudy conditions. IEEE Trans Geosci Remote Sens 41:390–409

    Article  Google Scholar 

  • Susskind J, Barnet C, Blaisdell J, Iredell L, Keita F, Kouvaris L, Molnar G, Chahine M (2006) Accuracy of geophysical parameters derived from Atmospheric Infrared Sounder/advanced microwave sounding unit as a function of fractional cloud cover. J Geophys Res 111:D09S17. doi:10.1029/2005JD006272

    Article  Google Scholar 

  • Thiebaux J, Rogers E, Wang W, Katz B (2003) A new high resolution blended real-time global sea surface temperature analysis. Bull Am Meteor Soc 84:645–656

    Article  Google Scholar 

  • Tian B, Waliser DE, Fetzer EJ, Lambrigtsen BH, Yung YL, Wang B (2006) Vertical moist thermodynamic structure and spatial-temporal evolution of the MJO in AIRS observations. J Atmos Sci 63:2462–2485

    Article  Google Scholar 

  • Tobin DC, Revercomb HE, Knuteson RO, Lesht BM, Strow LL, Hannon SE, Feltz WF, Moy LA, Fetzer EJ, Cress TS (2006) Atmospheric radiation measurement site atmospheric state best estimates for Atmospheric Infrared Sounder temperature and water vapor retrieval validation. J Geophys Res 111:D09S14. doi:10.1029/2005JD006103

    Google Scholar 

  • Wilks D (2006) Statistical methods in the atmospheric sciences: an introduction, 2nd edn. Academic Press, Cambridge

    Google Scholar 

  • Wong S, Fetzer EJ, Tian B, Lambrigtsen B (2011) The apparent water vapor sinks and heat sources associated with the intraseasonal oscillation of the Indian summer monsoon. J Clim 24:4466–4479

    Article  Google Scholar 

  • Xavier PK, Marzin C, Goswami BN (2007) An objective definition of the Indian summer monsoon season and a new perspective on ENSO-monsoon relationship. Q J Meteorol Soc 133:749–764

    Article  Google Scholar 

  • Xavier VF, Chandrasekar A, Rahman H, Niyogi D, and Alapaty K (2008) The effect of satellite and conventional meteorological data assimilation on the mesoscale modeling of monsoon depressions over India. Meteorol Atmos Phys 101:65–92

    Article  Google Scholar 

  • Zavodsky BT, Chou S, Jedlovec GJ (2012) Improved regional analyses and heavy precipitation forecasts with assimilation of Atmospheric Infrared Sounder retrieved thermodynamic profiles. IEEE Trans Geosci Remote Sens 50(11):4243–4251

    Article  Google Scholar 

  • Zhou YP, Lau KM, Reale O, Rosenberg R (2010) AIRS impact on precipitation analysis and forecast of tropical cyclones in a global data assimilation and forecast system. Geophys Res Lett 37:L02806. doi:10.1029/2009GL041494

    Article  Google Scholar 

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Acknowledgements

We thank the Director of ESSO-IITM for support. We are grateful to the anonymous reviewers for constructive comments and valuable suggestions, which have helped us to substantially improve this article. We also thank Dr. Oreste Reale for his valuable suggestions, edits and comments on our manuscript. We thank Mr. Cesar Weston and Dr. P. R. C. Reddy for language editing. The authors are grateful to NCAR, Boulder, Colorado, USA for making the WRF-ARW model available. The AIRS data used in this study are obtained from the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) Distributed Active Archive Center (DAAC). Authors are thankful to ECMWF for reanalysis obtained from their data server. Thanks are also due to TRMM and GPCP for providing the rainfall data used in this study. Produced downscale reanalysis in this study is presently available on request basis later it may be provided on open access.

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  1. Raju Attada

    Present address: King Abdullah University of Science and Technology, Thuwal, Saudi Arabia

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  1. Theoretical Studies Division, Indian Institute of Tropical Meteorology, Pune, 411 008, India

    Raju Attada, Anant Parekh, J. S. Chowdary & C. Gnanaseelan

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Attada, R., Parekh, A., Chowdary, J.S. et al. Reanalysis of the Indian summer monsoon: four dimensional data assimilation of AIRS retrievals in a regional data assimilation and modeling framework. Clim Dyn 50, 2905–2923 (2018). https://doi.org/10.1007/s00382-017-3781-z

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