Study on the evolution of initial field error in the simulation of river flow 河流流場數(shù)值模擬初始場誤差發(fā)展研究
The initial field formed by 3dvar system is right and reasonable 三維變分?jǐn)?shù)據(jù)同化系統(tǒng)同化衛(wèi)星數(shù)據(jù)后,所形成的初值場是合理和正確的。
This paper presents an application of genetic algorithms ( gas ) to variational data assimilation for the initial fields 本文將遺傳算法應(yīng)用于初始場的變分同化中。
Adjoint method provides an efficient tool to calculate the gradient vector of the cost function to the initial field 利用伴隨方法,可以求出該度量函數(shù)關(guān)于初始場的梯度向量。
The forecasting of meteorological element fields and precipitation is improved by use of the adjusted initial field 使用調(diào)整后的初始場對降水及其它物理量場的預(yù)報(bào)均有所改善。
The optimal initial field not only meets the dynamical and thermal expectations but also reflects the true atmospheric state 最優(yōu)初始場,既要滿足模式動力和熱力要求,又能反映大氣的真實(shí)狀態(tài)。
Then adjust these data to needful format . and then combine t106 data , sst data and sur , uao meteorologic data to form initial field 結(jié)合t106資料、 sst資料以及地面、探空常規(guī)觀測資料,構(gòu)成初始場,進(jìn)行模擬。
The result shows that the mm5 adjoint - model assimilation system can effectively assimilate the conventional data and adjust the initial field 對比研究結(jié)果表明, mm5伴隨模式能有效同化常規(guī)觀測資料,調(diào)整初始場。
Then adjust these data to needful format . and then combine t106 data , sst data and sur , uao meteorologic data to form initial field 寫成模式需要的格式,結(jié)合t106資料、 sst資料以及地面、探空常規(guī)觀測資料,構(gòu)成初始場,進(jìn)行模擬。
Recently the development of numerical models has run to perfection , so whether the initial field stands to exactness counts 近年來,數(shù)值模式的發(fā)展相當(dāng)精細(xì),可以真實(shí)地描寫和模擬出實(shí)際天氣過程的演變發(fā)展,因而初始場是否精確就至關(guān)重要。