scholarly journals Effect of relative humidity and sea level pressure on electrical conductivity of air over Indian Ocean

2009 ◽  
Vol 114 (D2) ◽  
Author(s):  
S. D. Pawar ◽  
P. Murugavel ◽  
D. M. Lal
Keyword(s):  
Electrical Conductivity ◽  
Relative Humidity ◽  
Indian Ocean ◽  
Sea Level ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
And Sea Level

Dynamic Assimilation of MODIS-Retrieved Humidity Profiles within a Regional Model for High-Latitude Forecast Applications

2005 ◽  
Vol 133 (12) ◽  
pp. 3450-3480 ◽  
Author(s):  
Xingang Fan ◽  
Jeffrey S. Tilley
Keyword(s):  
Relative Humidity ◽  
Sea Level ◽  
High Latitude ◽  
Wind Pressure ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Hot Start ◽  
Numerical Experimentation ◽  
Humidity Profiles ◽  
And Sea Level

Abstract A “hot start” technique is applied to the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) to dynamically assimilate cloud properties and humidity profiles retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board the NASA Earth Observing System polar-orbiting satellites. The assimilation approach has been studied through extensive numerical experimentation for high-latitude rain events to demonstrate the feasibility and the benefit of the approach on the model cloud and precipitation simulation/forecast. The ingestion of MODIS-retrieved cloud and clear-air humidity information impacts MM5 cloud fields on both a microphysical and macrophysical level. From short-term (6–12 h) forecast experiments conducted for a preliminary test case and 16 extensive summer and winter experiments, the following primary conclusions have been reached. 1) It is feasible to introduce MODIS-retrieved cloud-top properties and humidity profiles into the MM5 model in a hot start mode without disrupting model stability and evolutionary continuity. 2) The introduction of high-resolution MODIS information produced more accurate humidity fields and resulted in increased mesoscale structure in the cloud and precipitation fields. 3) The opportunistic ingestion of MODIS data at its observation time into the model leads to improved 6–12-h model precipitation forecasts with respect to not only the frequency of occurrences, but also the magnitude of precipitation amounts. 4) Verification with three-dimensional analyses indicates some improvement in model forecasts of temperature, wind, pressure perturbation, and sea level pressure as well. 5) Verification with surface station observations indicates that model forecasts of 2-m temperature, 2-m relative humidity, 10-m winds, and sea level pressure are also improved, most notably for the summer cases. The largest improvement in forecast skill is for 2-m relative humidity (12%).

scholarly journals Does sea level pressure modulate the dynamic and thermodynamic forcing in the tropical Indian Ocean?

2011 ◽  
Vol 33 (7) ◽  
pp. 1991-2002 ◽  
Author(s):  
P. G. Nisha ◽  
P. M. Muraleedharan ◽  
M. G. Keerthi ◽  
P. V. Sathe ◽  
M. Ravichandran
Keyword(s):  
Indian Ocean ◽  
Sea Level ◽  
Tropical Indian Ocean ◽  
Sea Level Pressure ◽  
Level Pressure

scholarly journals Daily to intraseasonal oscillations at Antarctic research station Neumayer

2013 ◽  
Vol 26 (2) ◽  
pp. 193-204 ◽  
Author(s):  
N. Rimbu ◽  
G. Lohmann ◽  
G. König-Langlo ◽  
C. Necula ◽  
M. Ionita
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Sea Level ◽  
Intraseasonal Variability ◽  
Research Station ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Intraseasonal Oscillations ◽  
Antarctic Research ◽  
And Sea Level

AbstractHigh temporal resolution (three hours) records of temperature, wind speed and sea level pressure recorded at Antarctic research station Neumayer (70°S, 8°W) during 1982–2011 are analysed to identify oscillations from daily to intraseasonal timescales. The diurnal cycle dominates the three-hourly time series of temperature during the Antarctic summer and is almost absent during winter. In contrast, the three-hourly time series of wind speed and sea level pressure show a weak diurnal cycle. The dominant pattern of the intraseasonal variability of these quantities, which captures the out-of-phase variation of temperature and wind speed with sea level pressure, shows enhanced variability at timescales of ∼ 40 days and ∼ 80 days, respectively. Correlation and composite analysis reveal that these oscillations may be related to tropical intraseasonal oscillations via large-scale eastward propagating atmospheric circulation wave-trains. The second pattern of intraseasonal variability, which captures in-phase variations of temperature, wind and sea level pressure, shows enhanced variability at timescales of ∼ 35, ∼ 60 and ∼ 120 days. These oscillations are attributed to the Southern Annular Mode/Antarctic Oscillation (SAM/AAO) which shows enhanced variability at these timescales. We argue that intraseasonal oscillations of tropical climate and SAM/AAO are related to distinct patterns of climate variables measured at Neumayer.

scholarly journals Studying Recorded lightning over Iraq for Period 1998-2011

2018 ◽  
Vol 28 (3) ◽  
pp. 1
Author(s):  
Lena Mohammed Abbas
Keyword(s):  
Relative Humidity ◽  
Sea Level ◽  
Vertical Velocity ◽  
Mean Value ◽  
Sea Level Pressure ◽  
Mean Sea Level ◽  
Mean Values ◽  
Level Pressure ◽  
Special Cases ◽  
The Hours

This research studies distribution of thunderstorm in Iraq for the period (1998-2011), the result showed that  the largest regions which had been hit by lightning stroke were between latitude (35-36◦)E and longitude (45-46◦)N, and April was the most frequent of lightning occurrence, also the results showed  that the number of flashes of most lightning cases were between (50-100) with higher number of flashes for some special cases. The studying of meteorological parameters which accompanied thunderstorm formation such as (Mean sea level pressure, Lifting index, relative humidity and Vertical velocity) illustrates the values of mean sea level pressure were increased during the hours after lightning occurrence comparing with their values before and at the time of lightning occurrence and their monthly mean value much greater than that recorded at the time of lightning occurrence, in addition the values of lifting index were negative at the time of lightning occurrence that refer to instability whereas their monthly average showed positive values. The values of relative humidity were greater at lightning recorded time at the three levels (500, 700, 1000)mb and also through the hours before and after this time comparing with their monthly mean. Vertical velocity values were negative for the three levels at the time of lightning occurrence that is referring to upward motion which is necessary for thundercloud initiation, and their monthly mean values were mostly negative at (500, 700)mb whereas were positive at the surface level

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