On the impact of humidity observations in numerical weather prediction

Tellus, Series A: Dynamic Meteorology and Oceanography

Volumn 57, Issue 5, 2005, Pages 701-708

  Bengtsson, Lennart ^a   Hodges, Kevin I ^a  

^a UNIVERSITY OF READING   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

AIR TEMPERATURE; DATA ASSIMILATION; GEOPOTENTIAL; RELATIVE HUMIDITY; WEATHER FORECASTING;

EID: 27744489378     PISSN: 02806495     EISSN: 16000870     Source Type: Journal    
DOI: 10.1111/j.1600-0870.2005.00142.x     Document Type: Article

References (18)

1. Bengtsson, L. 2001. Numerical modelling of the energy and water cycle of the Baltic Sea. Meteorol. Atmos. Phys. 77, 9-17.
2. Bengtsson, L. and Arpe, K. 2000. Wasser im Klimasystem. In: Wasser (eds B. Busch, and L. Förster). Kunst- und Ausstellungshalle der Bundesrepublik Deutschland. Wienand Verlag, Bonn und Köln, pp. 116-123.
3. Bengtsson, L., Hodges, K. and Hagemann, S. 2004a. Sensitivity of large-scale atmospheric analyses to humidity observations and its impact on the global water cycle and tropical and extratropical weather systems in ERA-40. Tellus 56A, 202-217.
4. Bengtsson, L., Hodges, K. and Hagemann, S. 2004b. Sensitivity of the ERA-40 reanalysis to the observing system: Determination of the global atmospheric circulation from reduced observations. Tellus 56A, 456-471.
5. Hagemann, S., Machenhauer, B., Jones, R., Christensen, O. B., Deque, M. and co-authors. 2004. Evaluation of water and energy budgets in regional climate models applied over Europe. Climate Dyn. 23, 547-567.
6. Hólm, E., Andersson, E., Beljaars, A., Lopez, P., Mahfouf, J.-F. and co-authors. 2002. Assimilation and modelling of the hydrological cycle: ECMWF's status and plans. ECMWF Technical Memo 383, ECMWF, Shinfield Park, Reading, RG2 9AX, UK
7. Jacob, D. 2001. A note to the simulation of the annual and interannual variability of the water budget over the Baltic Sea drainage basin. Meteorol. Atmos. Phys. 77, 61-73.
8. Kamineni, R., Krishnamurti, T. N., Ferrare, R. A., Ismail, S. and Browell, E. V. 2003. Impact of high-resolution water vapour cross-sectional data on hurricane forecasting. Geophys. Res. Lett. 30, 1234 (doi:).
9. Krishnamurti, T., Xue, N., Bedi, J. H. S., Ingles, K. and Oosterhof, D. 1991. Physical initialization for numerical weather prediction over the tropics. Tellus 43AB, 53-81.
10. Lorenz, E. N. 1982. Atmospheric predictability experiments with a large numerical model. Tellus 34, 505-513.
11. Mahfouf, J.-F., Bauer, P. and Marécal, V. 2003. The assimilation of SSM/I and TMI rainfall rates in the ECMWF 4DVar System. ECMWF Technical Memo 429, ECMWF, Shinfield Park, Reading, RG2 9AX, UK.
12. Phillips, N. A. 1973. Principles of large-scale numerical weather prediction. In: Dynamic Meteorology (ed. P. Morel). Reidel, Dortrecht.
13. Simmons, A. J. and Gibson, J. K. 2000. The ERA-40 Project Plan. ERA-40 Project Report Series No. 1 ECMWF, Shinfield Park, Reading, UK, 63 pp.
14. Simmons, A. J. and Hollingsworth, A. 2002. Some aspects of the improvement in skill of numerical weather prediction. Q. J. R. Meteorol. Soc. 128, 647-677.
15. Smagorinsky, J., Miyakoda, K. and Strickler, R. F. 1970. The relative importance of variables in initial conditions for dynamical weather prediction. Tellus 22, 141-157.
16. Temperton, C. 1976. Dynamic initialization for barotropic and multilevel models. Q. J. R. Meteorol. Soc. 102, 297-311.
17. Wang, X. L. and Zwiers, F. W. 1999. Interannual variability of precipitation in an ensemble of AMIP climate simulations conducted with the CCC GCM2. J. Climate 12 (5), 1322-1335.
18. White, P. 2000. IFS Documentation Part III: Dynamics and Numerical Procedures (CY21R4). Meteorological Bulletin M1.6/4, ECMWF, Shinfield Park, Reading, UK.