Surface Water and Energy Budgets for the Mississippi River Basin in Three NCEP Reanalyses

Rongqian Yang Environmental Modeling Center, NOAA/NWS/NCEP, College Park, and I.M. Systems Group, Inc., Rockville, Maryland

Search for other papers by Rongqian Yang in
Current site
Google Scholar
PubMed
Close
,
Michael Ek Environmental Modeling Center, NOAA/NWS/NCEP, College Park, Maryland

Search for other papers by Michael Ek in
Current site
Google Scholar
PubMed
Close
, and
Jesse Meng Environmental Modeling Center, NOAA/NWS/NCEP, College Park, and I.M. Systems Group, Inc., Rockville, Maryland

Search for other papers by Jesse Meng in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Surface water and energy budgets from the National Centers for Environmental Prediction–U.S. Department of Energy (NCEP–DOE) Atmospheric Model Intercomparison Project (AMIP-II) Global Reanalysis 2 (GR2), the North American Regional Reanalysis (NARR), and the NCEP Climate Forecast System Reanalysis (CFSR) are compared here with each other and with available observations over the Mississippi River basin. The comparisons in seasonal cycle, interannual variation, and annual mean over a 31-yr period show that there are a number of noticeable differences and similarities in the large-scale basin averages. Warm season precipitation and runoff in the GR2 are too large compared to the observations, and seasonal surface water variation is small. By contrast, the precipitation in both NARR and CFSR is more reasonable and in better agreement with the observation, although the corresponding seasonal runoff is very small. The main causes of the differences in both surface parameterization and approach used in assimilating the observed precipitation datasets and snow analyses are then discussed. Despite the discrepancies in seasonal water budget components, seasonal energy budget terms in the three reanalyses are close to each other and to available observations. The interannual variations in both water and energy budgets are comparable. This study shows that the CFSR achieves a large improvement over the GR2, indicating that the CFSR dataset can be used in climate variability studies. Nonetheless, improved land surface parameterization schemes and data assimilation techniques are needed to depict the surface water and energy climates better, in particular, the variation in seasonal runoff.

Corresponding author address: Dr. Rongqian Yang, Environmental Modeling Center, National Centers for Environmental Prediction, NOAA Center for Weather and Climate Prediction, 5830 University Research Ct., College Park, MD 20740. E-mail: rongqian.yang@noaa.gov

Abstract

Surface water and energy budgets from the National Centers for Environmental Prediction–U.S. Department of Energy (NCEP–DOE) Atmospheric Model Intercomparison Project (AMIP-II) Global Reanalysis 2 (GR2), the North American Regional Reanalysis (NARR), and the NCEP Climate Forecast System Reanalysis (CFSR) are compared here with each other and with available observations over the Mississippi River basin. The comparisons in seasonal cycle, interannual variation, and annual mean over a 31-yr period show that there are a number of noticeable differences and similarities in the large-scale basin averages. Warm season precipitation and runoff in the GR2 are too large compared to the observations, and seasonal surface water variation is small. By contrast, the precipitation in both NARR and CFSR is more reasonable and in better agreement with the observation, although the corresponding seasonal runoff is very small. The main causes of the differences in both surface parameterization and approach used in assimilating the observed precipitation datasets and snow analyses are then discussed. Despite the discrepancies in seasonal water budget components, seasonal energy budget terms in the three reanalyses are close to each other and to available observations. The interannual variations in both water and energy budgets are comparable. This study shows that the CFSR achieves a large improvement over the GR2, indicating that the CFSR dataset can be used in climate variability studies. Nonetheless, improved land surface parameterization schemes and data assimilation techniques are needed to depict the surface water and energy climates better, in particular, the variation in seasonal runoff.

Corresponding author address: Dr. Rongqian Yang, Environmental Modeling Center, National Centers for Environmental Prediction, NOAA Center for Weather and Climate Prediction, 5830 University Research Ct., College Park, MD 20740. E-mail: rongqian.yang@noaa.gov
Save
  • Auad, G., Miller A. J. , Roads J. O. , and Cayan D. , 2001: Pacific Ocean wind stress and surface heat flux anomalies from NCEP reanalysis and observation: Cross-statistics and ocean model responses. J. Geophys. Res., 106, 22 24922 265, doi:10.1029/2000JC000264.

    • Search Google Scholar
    • Export Citation
  • Baldwin, M. E., and Mitchell K. E. , 1997: The NCEP hourly multi-sensor U.S. precipitation analysis for operations and GCIP research. Preprints, 13th Conf. on Hydrology, Long Beach, CA, Amer. Meteor. Soc., 5455.

  • Barlage, M., and Coauthors, 2010: Noah land surface model modifications to improve snowpack prediction in the Colorado Rocky Mountains. J. Geophys. Res., 115, D22101, doi:10.1029/2009JD013470.

    • Search Google Scholar
    • Export Citation
  • Barlage, M., Tewari M. , Chen F. , Manning K. , and Miguez-Macho G. , 2013: North American regional climate simulations with WRF/Noah-MP validation and the effect of ground water interaction. Proc. 14th WRF User's Workshop, Boulder, CO, WRF. [Available online at www2.mmm.ucar.edu/wrf/users/workshops/WS2013/ppts/5B.2.pdf.]

    • Search Google Scholar
    • Export Citation
  • Berbery, E. H., and Rasmusson E. M. , 1999: Mississippi moisture budgets on regional scales. Mon. Wea. Rev.,127, 2654–2673, doi:10.1175/1520-0493(1999)127<2654:MMBORS>2.0.CO;2.

  • Berbery, E. H., Luo Y. , Mitchell K. , and Betts A. K. , 2003: Eta model–estimated land surface processes and the hydrologic cycle of the Mississippi basin. J. Geophys. Res., 108, 8852, doi:10.1029/2002JD003192.

    • Search Google Scholar
    • Export Citation
  • Betts, A., Hong S.-Y. , and Pan H.-L. , 1996: Comparison of NCEP–NCAR reanalysis with 1987 FIFE data. Mon. Wea. Rev., 124, 14801498, doi:10.1175/1520-0493(1996)124<1480:CONNRW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Betts, A., Viterbo P. , and Wood E. , 1998: Surface energy and water balance for the Arkansas–Red River basin from the ECMWF reanalysis. J. Climate, 11, 28812897, doi:10.1175/1520-0442(1998)011<2881:SEAWBF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Betts, A., Ball J. H. , and Viterbo P. , 1999: Basin-scale surface water and energy budgets for the Mississippi from the ECMWF reanalysis. J. Geophys. Res., 104, 19 29319 306, doi:10.1029/1999JD900056.

    • Search Google Scholar
    • Export Citation
  • Black, T., 1994: The new NMC mesoscale Eta model: Description and forecast examples. Wea. Forecasting, 9, 265278, doi:10.1175/1520-0434(1994)009<0265:TNNMEM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Brunke, M. A., Wang Z. , and Zeng X. , 2011: An assessment of the uncertainties in ocean surface turbulent fluxes in 11 reanalysis, satellite-derived, and combined global datasets. J. Climate,24, 5469–5493, doi:10.1175/2011JCLI4223.1.

  • Campana, K., and Caplan P. , 2005: Technical procedures bulletin for the T382 Global Forecast System. NOAA/NCEP/Environmental Modeling Center. [Available online at www.emc.ncep.noaa.gov/gc_wmb/Documentation/TPBoct05/T382.TPB.FINAL.htm.]

  • Chen, F., Mitchell K. , Schaake J. , Xue Y. , Pan H.-L. , Koren V. , Duan Q. , and Betts A. , 1996: Modeling of land surface evaporation by four schemes and comparison with FIFE observations. J. Geophys. Res., 101, 7251–7268, doi:10.1029/95JD02165.

    • Search Google Scholar
    • Export Citation
  • Chen, M., Shi W. , Xie P. , Silva V. B. S. , Kousky V. E. , Wayne Higgins R. , and Janowiak J. E. , 2008: Assessing objective techniques for gauge-based analyses of global daily precipitation. J. Geophys. Res., 113, D04110, doi:10.1029/2007JD009132.

    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, doi:10.1002/qj.828.

    • Search Google Scholar
    • Export Citation
  • Dole, R., Hoerling M. , and Schubert S. , Eds., 2008: Reanalysis of historical climate data for key atmospheric features: Implications for attribution of causes of observed change. U.S. Climate Change Science Program Synthesis and Assessment Product 1.3, NOAA, Asheville, NC, 156 pp.

  • Ek, M. B., Mitchell K. E. , Lin Y. , Rogers E. , Grunmann P. , Koren V. , Gayno G. , and Tarpley J. D. , 2003: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J. Geophys. Res., 108, 8851, doi:10.1029/2002JD003296.

    • Search Google Scholar
    • Export Citation
  • Gochis, D. J., and Chen F. , 2003: Implementation and testing of a grid-based routing scheme in the Noah land surface model. EGS–AGU–EUG Joint Assembly, Nice, France, EGU, Abstract 799.

  • Helfrich, S. R., McNamara D. , Ramsay B. H. , Baldwin T. , and Kasheta T. , 2007: Enhancements to and forthcoming developments in the Interactive Multisensor Snow and Ice Mapping System (IMS). Hydrol. Process., 21, 1576–1586, doi:10.1002/hyp.6720.

  • Hollinger, S. E., and Isard S. A. , 1994: A soil moisture climatology of Illinois. J. Climate, 7, 822827, 833, doi:10.1175/1520-0442(1994)007<0822:ASMCOI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Holtslag, A. A. M., and Ek M. , 1996: Simulation of surface fluxes and boundary layer development over the pine forest in HAPEX-MOBILHY. J. Appl. Meteor., 35, 202213, doi:10.1175/1520-0450(1996)035<0202:SOSFAB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Jacquemin, B., and Noilhan J. , 1990: Sensitivity study and validation of a land surface parameterization using the HAPEX-MOBILHY dataset. Bound.-Layer Meteor., 52, 93134, doi:10.1007/BF00123180.

    • Search Google Scholar
    • Export Citation
  • Jarvis, P. G., 1976: The interpretation of the variations in leaf water potential and stomatal conductance found in canopies in the field. Philos. Trans. Roy. Soc. London.,B273, 593–610, doi:10.1098/rstb.1976.0035.

    • Search Google Scholar
    • Export Citation
  • Ji, M., Leetmaa A. , and Derber J. , 1995: An ocean analysis system for seasonal to interannual climate studies. Mon. Wea. Rev., 123, 460481, doi:10.1175/1520-0493(1995)123<0460:AOASFS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Josey, S. A., 2001: A Comparison of ECMWF, NCEP–NCAR, and SOC surface heat fluxes with moored buoy measurements in the subduction region of the northeast Atlantic. J. Climate, 14, 17801789, doi:10.1175/1520-0442(2001)014<1780:ACOENN>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., 2000: The US reanalysis program: Climatology for the new millennium. Rep. of the First Planning Workshop for the Next US Global Reanalysis, University of Maryland, College Park, College Park, MD, 19 pp. [Available online at http://old.usclivar.org/Pubs/ReanalysisWorkshop_Rep.pdf.]

  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437470, doi:10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kanamitsu, M., and Coauthors, 2002: NCEP–DOE AMIP-II Reanalysis (R-2). Bull. Amer. Meteor. Soc., 83, 16311643, doi:10.1175/BAMS-83-11-1631.

    • Search Google Scholar
    • Export Citation
  • Kistler, R., and Coauthors, 2001: The NCEP–NCAR 50-Year Reanalysis: Monthly means CD-ROM and documentation. Bull. Amer. Meteor. Soc., 82, 247267, doi:10.1175/1520-0477(2001)082<0247:TNNYRM>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kopp, T. J., and Kiess R. B. , 1996: The Air Force Global Weather Central snow analysis model. Preprints, 15th Conf. on Weather Analysis and Forecasting, Norfolk, Virginia, Amer. Meteor. Soc., 220222.

  • Koren, V., Schaake J. , Mitchell K. , Duan Q.-Y. , Chen F. , and Baker J. M. , 1999: A parameterization of snowpack and frozen ground intended for NCEP weather and climate models. J. Geophys. Res., 104, 19 56919 585, doi:10.1029/1999JD900232.

    • Search Google Scholar
    • Export Citation
  • Koster, R., and Coauthors, 2004: Regions of strong coupling between soil moisture and precipitation. Science,305, 1138–1140, doi:10.1126/science.1100217.

  • Koster, R., Guo Z. , Yang R. , Dirmeyer P. A. , Mitchell K. E. , and Puma M. J. , 2009: On the nature of soil moisture in land surface models. J. Climate, 22, 43224335, doi:10.1175/2009JCLI2832.1.

    • Search Google Scholar
    • Export Citation
  • Liang, X., Lettenmaier D. P. , Wood E. F. , and Burges S. J. , 1994: A simple hydrologically based model of land surface water and energy fluxes for GSMs. J. Geophys. Res., 99, 14 41514 428, doi:10.1029/94JD00483.

    • Search Google Scholar
    • Export Citation
  • Lin, Y., Mitchell K. E. , Rogers E. , and DiMego G. J. , 2005: Using hourly and daily precipitation analyses to improve model water budget. Preprints, Ninth Symp. on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface, San Diego, CA, Amer. Meteor. Soc., 3.3. [Available online at http://ams.confex.com/ams/pdfpapers/84484.pdf.]

  • Livneh, B., Xia Y. , Mitchell K. E. , Ek M. B. , and Lettenmaier D. P. , 2010: Noah LSM snow model diagnostics and enhancements. J. Hydrometeor., 11, 721738, doi:10.1175/2009JHM1174.1.

    • Search Google Scholar
    • Export Citation
  • Lohmann, D., and Coauthors, 2004: Streamflow and water balance intercomparison of four land surface models in the North American Land Data Assimilation Systems project. J. Geophys. Res.,109, D07S91, doi:10.1029/2003JD003517.

  • Luo, Y., Berbery H. , Mitchell K. , and Betts A. , 2007: Relationships between land surface and near-surface atmospheric variables in the NCEP North American Regional Reanalysis. J. Hydrometeor., 8, 11841203, doi:10.1175/2007JHM844.1.

    • Search Google Scholar
    • Export Citation
  • Mahrt, L., and Ek M. , 1984: The influence of atmospheric stability on potential evaporation. J. Climate Appl. Meteor., 23, 222234, doi:10.1175/1520-0450(1984)023<0222:TIOASO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Mahrt, L., and Pan H.-L. , 1984: A two-layer model of soil hydrology. Bound.-Layer Meteor., 29, 120, doi:10.1007/BF00119116.

  • Matson, M., Ropelewski C. F. , and Varnadore M. S. , 1986: An Atlas of Satellite-Derived Northern Hemisphere Snow Cover Frequency. National Weather Service, 75 pp.

  • Maurer, E. P., O’Donnell G. , Lettenmaier D. , and Roads J. , 2001: Evaluation of the land surface water budget in NCEP/NCAR and NCEP/DOE reanalyses using an off-line hydrologic model. J. Geophys. Res., 106, 17 84117 862, doi:10.1029/2000JD900828.

    • Search Google Scholar
    • Export Citation
  • McNally, A. P., Derber J. C. , Wu W.-S. , and Katz B. B. , 2006: The use of TOVS level-1 radiances in the NCEP SSI analysis system. Quart. J. Roy. Metor. Soc, 126, 689724, doi:10.1002/qj.49712656315.

    • Search Google Scholar
    • Export Citation
  • Meng, J., Yang R. , Wei H. , Ek M. , Gayno G. , Xie P. , and Mitchell K. , 2012: The land surface analysis in the NCEP Climate Forecast System Reanalysis. J. Hydrometeor.,13, 1621–1630, doi:10.1175/JHM-D-11-090.1.

  • Mesinger, F., Janjić Z. I. , Nickovic S. , Gavrilov D. , and Deaven D. G. , 1988: The step-mountain coordinate: Model description and performance for cases of alpine lee cyclogenesis and for a case of an Appalachian redevelopment. Mon. Wea. Rev., 116, 1493–1518, doi:10.1175/1520-0493(1988)116<1493:TSMCMD>2.0.CO;2.

  • Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor. Soc., 87, 343360, doi:10.1175/BAMS-87-3-343.

    • Search Google Scholar
    • Export Citation
  • Milly, P. C. D., and Dunne K. A. , 2001: Trends in evaporation and surface cooling is the Mississippi River basin. Geophys. Res. Lett.,28, 1219–1222, doi:10.1029/2000GL012321.

  • Mitchell, K., and Coauthors, 2004: The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system. J. Geophys. Res., 109, D07S90, doi:10.1029/2003JD003823.

  • Music, B., and Caya D. , 2007: Evaluation of the hydrological cycle over the Mississippi River basin as simulated by the Canadian Regional Climate Model (CRCM). J. Hydrometeor., 8, 969988, doi:10.1175/JHM627.1.

    • Search Google Scholar
    • Export Citation
  • Niu, G.-Y., Yang Z.-L. , Dickinson R. E. , Gulden L. E. , and Su H. , 2007: Development of a simple groundwater model for use in climate models and evaluation with Gravity Recovery and Climate Experiment data. J. Geophys. Res., 112, D07103, doi:10.1029/2006JD007522.

    • Search Google Scholar
    • Export Citation
  • Niu, G.-Y., and Coauthors, 2011: The community Noah land surface model with multi-parameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. J. Geophys. Res., 116, D12109, doi:10.1029/2010JD015139.

    • Search Google Scholar
    • Export Citation
  • Noilhan, J., and Planton S. , 1989: A simple parameterization of land surface processes for meteorological models. Mon. Wea. Rev., 117, 536549, doi:10.1175/1520-0493(1989)117<0536:ASPOLS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Onogi, K., and Coauthors, 2007: The JRA-25 Reanalysis. J. Meteor. Soc. Japan, 85, 369432, doi:10.2151/jmsj.85.369.

  • Pan, H.-L., and Mahrt L. , 1987: Interaction between soil hydrology and boundary-layer development. Bound.-Layer Meteor., 38, 185202, doi:10.1007/BF00121563.

    • Search Google Scholar
    • Export Citation
  • Peixóto, J. P., and Oort A. H. , 1983: The atmospheric branch of the hydrological cycle and climate. Variations of the Global Water Budget, D. Reidel, 5–65, doi:10.1007/978-94-009-6954-4_2.

  • Rienecker, M., and Coauthors, 2011: MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications. J. Climate, 24, 36243648, doi:10.1175/JCLI-D-11-00015.1.

    • Search Google Scholar
    • Export Citation
  • Roads, J., and Betts A. , 2000: NCEP–NCAR and ECMWF reanalysis surface water and energy budgets for the Mississippi River basin. J. Hydrometeor., 1, 8894, doi:10.1175/1525-7541(2000)001<0088:NNAERS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Roads, J., Chen S. , Kanamitsu M. , and Juang H. , 1999: Surface water characteristics in the NCEP global spectral model and reanalysis. J. Geophys. Res., 104, 19 30719 327, doi:10.1029/98JD01166.

    • Search Google Scholar
    • Export Citation
  • Roads, J., Kanamitsu M. , and Stewart R. , 2002: CSE water and energy budgets in the NCEP–DOE Reanalysis II. J. Hydrometeor., 3, 227248, doi:10.1175/1525-7541(2002)003<0227:CWAEBI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Roads, J., and Coauthors, 2003: GCIP water and energy synthesis (WEBS). J. Geophys. Res.,108, 8609, doi:10.1029/2002JD002583.

  • Robock, A., and Coauthors, 2000: The Global Soil Moisture Data Bank. Bull. Amer. Meteor. Soc.,81, 1281–1299, doi:10.1175/1520-0477(2000)081<1281:TGSMDB>2.3.CO;2.

  • Rodell, M., and Coauthors, 2004: The Global Land Data Assimilation System. Bull. Amer. Meteor. Soc., 85, 381394, doi:10.1175/BAMS-85-3-381.

    • Search Google Scholar
    • Export Citation
  • Saha, S., and Coauthors, 2010: The NCEP Climate Forecast System Reanalysis. Bull. Amer. Meteor. Soc.,91, 1015–1057, doi:10.1175/2010BAMS3001.1.

  • Saha, S., and Coauthors, 2014: The NCEP Climate Forecast System version 2. J. Climate, 27, 21852208, doi:10.1175/JCLI-D-12-00823.1.

  • Schaake, J. C., Koren V. I. , Duan Q.-Y. , Mitchell K. , and Chen F. , 1996: Simple water balance model for estimating runoff at different spatial and temporal scales. J. Geophys. Res., 101, 74617475, doi:10.1029/95JD02892.

    • Search Google Scholar
    • Export Citation
  • Seager, R., and Henderson N. , 2013: Diagnostic computation of moisture budgets in the ERA-Interim Reanalysis with reference to analysis of CMIP-archived atmospheric model data. J. Climate, 26, 78767901, doi:10.1175/JCLI-D-13-00018.1.

    • Search Google Scholar
    • Export Citation
  • Sheffield, J., Livneh B. , and Wood E. F. , 2012: Representation of terrestrial hydrology and large-scale drought of the continental United States from the North American Regional Reanalysis. J. Hydrometeor., 13, 856876, doi:10.1175/JHM-D-11-065.1.

    • Search Google Scholar
    • Export Citation
  • Srinivasan, G., and Coauthors, 2000: Soil moisture simulations in revised AMIP models. J. Geophys. Res., 105, 26 63526 644, doi:10.1029/2000JD900443.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., Fasullo J. T. , and Mackaro J. , 2011: Atmospheric moisture transports from ocean to land and global energy flows in reanalyses. J. Climate,24, 4907–4924, doi:10.1175/2011JCLI4171.1.

  • Uppala, S., and Coauthors, 2005: The ERA-40 re-analysis. Quart. J. Roy. Meteor., 131, 29613012, doi:10.1256/qj.04.176.

  • Wang, F., Wang L. , Koike T. , Zhou H. , Yang K. , Wang A. , and Li W. , 2011: Evaluation and application of a fine-resolution global data set in a semiarid mesoscale river basin with a distributed biosphere hydrological model. J. Geophys. Res., 116, D21108, doi:10.1029/2011JD015990.

    • Search Google Scholar
    • Export Citation
  • Wang, L., and Coauthors, 2009: Development of a distributed biosphere hydrological model and its evaluation with the Southern Great Plains Experiments (SGP97 and SGP99). J. Geophys. Res., 114, D08107, doi:10.1029/2008JD010800.

    • Search Google Scholar
    • Export Citation
  • Xie, P., and Arkin P. A. , 1997: Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Amer. Meteor. Soc., 78, 2539–2558, doi:10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2.

  • Xie, P., Chen M. , Yatagai A. , Hayasaka T. , Fukushima Y. , and Yang S. , 2007: A gauge based analysis of daily precipitation over East Asia. J. Hydrometeor., 8, 607626, doi:10.1175/JHM583.1.

    • Search Google Scholar
    • Export Citation
  • Yang, R., Mitchell K. E. , Meng J. , and Ek M. , 2011: Summer-season forecast experiments with the NCEP Climate Forecast System using different land models and different initial land states. J. Climate,24, 2319–2334, doi:10.1175/2010JCLI3797.1.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 405 101 5
PDF Downloads 256 57 1