Short-Term versus Climatological Relationship between Precipitation and Tropospheric Humidity

2012 ◽  
Vol 25 (22) ◽  
pp. 7983-7990 ◽  
Author(s):  
Hirohiko Masunaga

Abstract In this study the observed relationship of precipitation with column relative humidity (CRH), a metric of tropospheric humidity, is examined in order to address a known discrepancy inherent to past studies. A composite analysis of satellite data is carried out to explore the short-term (i.e., from hourly to daily) atmospheric variability for comparison with the climatology, hypothesizing that a primary cause for the discrepancy arises from a difference in the time scale of interest. The analysis is broken down into four classes on the basis of the degree of convective organization, ranging from unorganized shallow cumuli to highly organized convective systems. The CRH–precipitation relationship is found to be extremely nonlinear for the short-term variability, while the nonlinearity weakens to some degree when different convective systems in diverse humidity environments are averaged together into climatology. The weak exponential rise in the climatological CRH–precipitation curve occurs because highly organized convective systems become more frequent and intense and thus receive increasing weight in the climatological mean as the environment moistens.

2017 ◽  
Vol 52 (10) ◽  
pp. 1355-1362 ◽  
Author(s):  
Jakob Usemann ◽  
Désirée Demann ◽  
Pinelopi Anagnostopoulou ◽  
Insa Korten ◽  
Olga Gorlanova ◽  
...  

Author(s):  
Kaj M. Hansen ◽  
Jesper H. Christensen ◽  
Jørgen Brandt ◽  
Lise M. Frohn ◽  
Camilla Geels ◽  
...  

2013 ◽  
Vol 6 (2) ◽  
pp. 3581-3610
Author(s):  
S. Federico

Abstract. This paper presents the current status of development of a three-dimensional variational data assimilation system. The system can be used with different numerical weather prediction models, but it is mainly designed to be coupled with the Regional Atmospheric Modelling System (RAMS). Analyses are given for the following parameters: zonal and meridional wind components, temperature, relative humidity, and geopotential height. Important features of the data assimilation system are the use of incremental formulation of the cost-function, and the use of an analysis space represented by recursive filters and eigenmodes of the vertical background error matrix. This matrix and the length-scale of the recursive filters are estimated by the National Meteorological Center (NMC) method. The data assimilation and forecasting system is applied to the real context of atmospheric profiling data assimilation, and in particular to the short-term wind prediction. The analyses are produced at 20 km horizontal resolution over central Europe and extend over the whole troposphere. Assimilated data are vertical soundings of wind, temperature, and relative humidity from radiosondes, and wind measurements of the European wind profiler network. Results show the validity of the analysis solutions because they are closer to the observations (lower RMSE) compared to the background (higher RMSE), and the differences of the RMSEs are consistent with the data assimilation settings. To quantify the impact of improved initial conditions on the short-term forecast, the analyses are used as initial conditions of a three-hours forecast of the RAMS model. In particular two sets of forecasts are produced: (a) the first uses the ECMWF analysis/forecast cycle as initial and boundary conditions; (b) the second uses the analyses produced by the 3-D-Var scheme as initial conditions, then is driven by the ECMWF forecast. The improvement is quantified by considering the horizontal components of the wind, which are measured at a-synoptic times by the European wind profiler network. The results show that the RMSE is effectively reduced at the short range (1–2 h). The results are in agreement with the set-up of the numerical experiment.


2015 ◽  
Vol 29 (8) ◽  
pp. 1145-1164 ◽  
Author(s):  
Samuel T. Wilson ◽  
Benedetto Barone ◽  
Francois Ascani ◽  
Robert R. Bidigare ◽  
Matthew J. Church ◽  
...  

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