Researches Of Latent Heat Physical Retrieval Algorithms In Warm Rain System Based On WRF Model

Latent heat from precipitation is the main energy source for driving regional and global atmospheric circulation. Accurately evaluating the vertical structure of latent heat is the prerequisite to understand the weather phenomenon in different scalses like the Walker Circulation, El Nino and Southern Oscillation (ENSO for short), Monsoon, the tropical Pacific 30-60 days of the low-frequency oscillation (Madden-Julian oscillation, MJO for short), typhoons and frontal and so on.Currently most the retrieval algorithms of latent heat based on satellite observations still use LUT (Look-Up Table) methods. These algorithms have great dependence on CRM (Cloud Resolving Model) and can not adequately explore the physical connections between latent heat and the atmospheric measureable variables (cloud profile and precipitation profile etc). Recent latent heat inversion of physical algorithm (CPPROF), which developed the connections between latent heat and cloud, precipitation profile based on cloud physics, fully used the high resolution informations of cloud and precipitation profiles based on satellite observations. CPPROF has less dependence on CRM and good inversion results. However, this algorithm needs improvements on the sensitivity test of model and the practical aspects.Firstly this paper illustrates the necessity to develop the latent heat inversion of physics algorithms by analyzing and examining the uncertainty of the latent heat products based on satellite retrieval (using TRMM 2A12 as an example); secondly this paper proposed the direction to improve the retrieval algorithm based on the correlationship test between latent heat and multiple atmospheric measureable variables by using the simulation of WRF model; thirdly this paper test the sensitivity of the CPPROF algorithm under different microphysical schemes and found the universal properties in different microphysical schemes; finally, we developed a LUT retrieval algorithm of cloud water content from warm rain based on cloud top height (Cloud Top Height, referred CTH), cloud water path (Cloud Water Path, called CWP) and near-surface precipitation rate (Near Surface Rain Rate, referred NSRR) with the WRF simulations from global different precipitation area on warm cloud system. The results obtained are as follows:(1) The examination and evaluation about the latent heat profile datasets based on satellite retrievalDue to the difficults of evaluating latent heat profiles directly, this paper first matched and merged the datasets from TRMM 2A12,1B11 (Microwave Imager data) and 1B01 (visible and near-infrared scanner data). Then we discriminated the cloud phase and cloud top height information by using the infrared and microwave signals from the merge data. Finally we fulfilled the purpose of evalution the vertical structures of latent heat profile by analyzing the reasonableness of cloud water profile from 2A12 data.From the study of two typhoon cases, we found that, the profiles of precipitation ice cloud from 2A12 data was reasonable. The precipitation ice clouds is deep. Latent heat profiles showed a significant heating patterns from convective rain. Statistics from multiply typhoons in year 2001 to 2012 showed that the reasonable proportion of precipitation ice clouds is more than 70%.Most uncertain precipitation ice clouds are cirrus clouds or stratus clouds with thin cloud depth and little cloud cover.2A12 would often identify them to warm clouds. Statistics from multiply typhoons in year 2001 to 2012 showed that the reasonable proportion of ice clouds with uncertain precipitation was below 1%.In precipitation warm cloud, although it showed high brightness temperature from infrared channel (>278K) and weak microwave scattering signals from ice particles (>280K),2A12 data still would identify them to ice clouds. Statistics showed the proportion is not high (less than 10%).Statistics from multiply typhoon cases of 12 years showed with the lower of infrared brightness temperature (higher of cloud top height), cloud liquid water content, cloud ice water content and the heating of latent heat profiles will correspondingly increases, but the 2A12 data could not represent the difference of cloud top height with similar patterns of cloud or latent heat profile.(2) The correlation between latent heat and different atmospheric measureable variablesBased on the simulation of typhoon CHABA on its mature stage by WRF model, this paper investigated the distributions of different type latent heat and atmospheric measureable variables and examined the sensitivity of latent heat to atmospheric measureable variables, such as cloud water content (CWC for short), rain rate (Rr for short), vertical velocity (W for short), precipitation rate with the first derivative on height (dRr/dz), and so on.The cloud of convective rain is deep. CWC mainly is in the layer below the frozen layer and latent heat is released mainly from condensation of water vapor. Cloud bottom height of stratiform rain is high with latent heat release mainly from the vapor deposition process above the frozen layer and consumption from vaporation below the frozen layer. Warm rain cloud is shallow with weak convection and latent heat release.The sensitivity test of latent heat and atmospheric observable variables showed that the latent heat of condensation has a strong correlation with CWC, Rr, W and dRr/dz, where W is the strongest correlation with a correlation coefficient of up to 0.9 (convective precipitation); evaporation rate has a great relationship with temperature and humidity of environments of cloud or rain water, so the relationship of Rr, W, dRr/dz is not high.(3) The sensitivity of the latent heat retrieval by CPPROF algorithm with the different microphysical schemes in WRF modelThis paper simulated five experiments in the typhoon CHABA by using different microphysical parameterization schemes in WRF model to examine the sensitivity between latent heat and rain growth process in different microphysics schemes, we concluded that the latent heat of condensation and rain growth process in different microphysics schemes agreed very well. The average relationships of condensation latent heat and rain growth process in different type rain system and different microphysical schemes are very close except convective rain of MORRISON microphysical scheme.The retrieval results of using the parameterization method of condensation latent heat from CPPROF algorithm in different microphysical scheme tests showed that, the parameterization method of condensation latent heat from CPPROF algorithm can catch the main features of the latent heat compared with the model true results. The time-space average profile of latent heat has a similar pattern with model simulations. Therefore, latent heat parameterization method from CPPROF algorithm does not depend on any specified microphysical scheme or cloud resolving model. It is reasonable that the algorithm can be transplanted from two-dimensional model to the three-dimensional model (WRF).(4) The retrieval of cloud water content from water warm rain systemThis paper simulated nine tests of different warm rain system in the ocean area with low latitude all over the world and created a look-up table of cloud water content in warm rain. Statistical analysis showed that the location and shape of CWC profile was greatly constrained by the three cloud parameter of CTH, cloud bottom height (CBH for short) and CWP. The standard deviation of cloud water profile database is very small with the value even no more than 0.001 g/m3. Then we retrieved the CD (Cloud Depth) or CBH by CTH, CWP and NSRR. It showed that in different microphysical schemes and different rain systems, the CD inversion results were very consistent with model "true" values.The examinations and investigations of this cloud water profile retrieval algorithm in different microphysics scheme, different rain systems and CloudSat satellite observation data showed that the algorithm is accurate and credible. Although cloud water microphysics parameterization scheme is different, in different rain systems the dynamical and thermal conditions is vary widely, the retrieval of CWC profile can be consistent with the pattern of model "true" values in the evaluation of different scales.