جستجوی مقالات مرتبط با کلیدواژه « rainfall » در نشریات گروه « فیزیک »

Meteorological radars estimate the precipitation using a reflection-precipitation relation as Z=aRb with a، b coefficients. These coefficients will change from one precipitation to the other one. For the Tehran radars they are considered as a=200 and b=1. 6. These values are proper when we have moderate precipitations. This assumption causes an error in the estimation of different precipitation which is done by radars. In order to know how the evaluations of rain are done by Tehran radars، we consider the amount of rain in three chosen rain recording stations which are Qom، Kooshk Nosrat and Pakdasht. Our aim of these studies is to evaluate the estimation of the Tehran meteorological radars for different amounts of precipitations. Therefore three intervals، including 11/1/2010-11/4/2010، 1/8/2011-1/11/2011 and 1/15/2011-1/18/2011 have been chosen in which the precipitations have been reported. The primary results indicate that Tehran meteorological radars estimate the amount of the precipitation less than the amounts which are registered by the rain – gauge of meteorological stations. These differences become more when the precipitation rates are considered. To amend the estimated values of the precipitation which are taken by Tehran radars، these amounts are evaluated by data which are given by rain recovery stations and finally are rescaled by the logarithmic relation Z-R. Using this relation new values for the concerned coefficients are obtained for different dates of precipitation. After depicting the linear regression equation and getting new coefficients to estimate the intensity of rain، we can access to a plot which indicates how the precipitation will change by employing the required corrections. We are also able to plot the precipitation changes in the used rain recording stations. The results indicate that we achieve good progress of estimations if we use new coefficients. Comparison of the gathered rain data by radars with the data of the rain recording stations shows a 40% agreement between them. If we use new coefficients، this agreement will increase to 90% which confirm that these new coefficients are appropriate in the evaluation equation of precipitation. Results of this study illustrated that the error of the radar lies in two factors، the first one is that the raindrops absorb some of the radar signals and this causes that return signals to be reduced; therefore more rainfall intensity، weakens the wave reflections The second reason is that the reflectivity values are proportion to sixth power of raindrops diameters and this means that the reflection of radar waves is affected by the droplet size and the larger droplet diameter increases the reflection، while the rainfall measured by rain gauge is not affected by droplet size، and value of the recorded rainfall or precipitation volume is not affected. In other words، the radar estimates precipitation more than the actual amount occurring in rainfall with larger drop size while estimates are less than the actual amount of precipitation in rainfall with smaller drop size.

Increased concentration of greenhouse gases is expected to alter the radiative balance of atmosphere, causing increases in temperature and changes in precipitation patterns and other climatic variables. These changes are associated with the changes in hydrological systems globally and at the basin scale. These changes include: precipitation patterns and extremes; the amount and generation of river flow; the frequency and intensity of flood and drought. At present, coupled Atmospheric -Oceanic General Circulation Models (AOGCMs) are the most frequently used models for projection of different climatic change scenarios. These scenarios can finally simulate other changes, such as water resources changes in the future. The basis of these models consists of describing the physical processes taking place in the climate system and the dynamics of climate variables as a function of different internal or external changes. Up to now IPCC has released 4 different versions of AOGCM models including: First Assessment Report models (FAR) in 1990, Second Assessment Report models (SAR) in 1996, Third Assessment Report models (TAR) in 2001 and Fourth Assessment Report models (AR4) in 2007. In this paper we evaluate the uncertainty of using different TAR and AR4 AOGCM models on the projection of runoff of a basin. At first we used temperature and precipitation variables of 7 TAR models including CCSR, CGCM2, CSIRO-MK2, ECHAM4, GFDL-R30, HadCM3, NCAR-DOE PCM and 9 AR4 models including; CCSM3, GCM3, CSIRO Mk3, GFDL CM2.1, GISS E-R, HadCM3, ECHAM5, MIROC-med, PCM for the 2040-2069 periods under A2 emission scenario. The A2 scenario corresponds to pessimistic future with higher population growth, lower GDP growth, and fragmented and slower technological change. A conceptual rainfall-runoff model (SYMHYD) was calibrated and verified for the Gharesu basin in baseline period (1971-2000). SIMHYD simulates daily runoff (Surface runoff and base flow) using daily precipitation and potential evapotranspiration (PET) as input data. Gharesu basin is located in North West of great Karkheh River Basin, west of Iran. Historical data in this study are daily temperature (T), precipitation (P) and runoff (R) for thirty years period (1971 to 2000). These data were acquired from different sources and stations. Temperature records of Kermanshah synoptic station, Outflow measurements of Qarehbaghestan hydrometric station, and daily precipitation records of eleven rain gauge stations were used in this study. The climate variables (monthly temperature and precipitation) of 16 AOGCMs were downscaled to Gharesu basin. Downscaling is a procedure that derives local or regional scale information from larger scale data like AOGCM outputs. In this study, change factor downscaling techniques was employed to generate monthly precipitation and temperature values for Gharesu basin scale in future period (2040-2069). Results show that in all months the temperature of the basin will increase by an average of 2.5°C. On the other hand the increasing of temperature simulated by TAR models are more than AR4 models. Both AR4 and TAR models simulate precipitation in a same manner, reduction for winter and spring and increase for autumn. Finally the ranges of precipitation and temperature change of the period 2040-2069 simulated by both models introduced to SYMHYD rainfall-runoff model and the monthly runoff changes of the basin were simulated for the period 2040-2069 relative to the period 1971-2000. Results show that runoff change of the basin due to AR4 models are less than TAR models for most of the months. On the other hand the runoff will increase in winter by 20-60% and by 20-40% in summer and decrease in autumn up to 40% and up to 60% in spring. Finally it can be concluded that although the number of AR4 models used in this study is more than TAR models, the range of uncertainty of AR4 is less than TAR. The final results showed that the projections of AR4 models are more reliable than TAR models.