Relaxed Arakawa-Schubert Scheme Research Articles

Implementation of the Unified Representation of Deep Moist Convection in the CWBGFS

AbstractThis study implements the unified parameterization (UP) in the Central Weather Bureau Global Forecast System (CWBGFS) based on the relaxed Arakawa–Schubert scheme (RAS) at a horizontal resolution of 15 km. The new cumulus parameterization that incorporates the UP framework is called URAS. The UP generalizes the representation of moist convection between the parameterized and the explicitly resolved processes according to the process-dependent convective updraft fraction (σ). Short-term hindcasts are performed to investigate the impacts of the UP on the simulated precipitation variability and organized convective systems over the Maritime Continent when multiple scales of convection occurred. The result shows that σ is generally larger when convective systems develop, which adaptively reduces the parameterized convection and increases the spatial variation of moisture. In the URAS experiment, the moisture hotspots within organized convective systems contribute to the enhanced local circulation and the more significant variability of precipitation. Consequently, the URAS has a more realistic precipitation spectrum, an improved relationship between the maximum precipitation and the horizontal scale of the convective systems, and an improved column water vapor–precipitation relationship.

Sensitivity of summer precipitation in regional spectral model simulations over eastern China to physical schemes: Daily, extreme and diurnal cycle

In this study, the capability of the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM) in reproducing the precipitation in eastern China is evaluated with the simulation of 25‐year (1983–2007) summertime climate driven by the NCEP‐Department of Energy reanalysis. The impacts of different physical schemes on daily precipitation, diurnal cycle and precipitation extremes are studied through detailed analyses. The results show that the RSM model can reproduce the precipitation characteristics over eastern China, and the results are sensitive to the internal model physics and spectral nudging method. The cloud water prediction scheme of CLD3 (CLDn, the cloud schemes, classified according to the complexity microphysical processes) and the modified version of the Kain‐Fritsch scheme (KF2) tend to overestimate the summer precipitation by reproducing higher humidity, while the CLD1 and the Relaxed Arakawa Schubert scheme (RAS) always underestimate it. It is also demonstrated that RSM has the capability to reproduce the spatial distributions of the extreme precipitation intensity and duration. The physical schemes have great impact on the simulations of extreme precipitation over eastern China, especially on regional scales. For the diurnal cycle of precipitation, the responses of the simulated amplitude to the physical schemes differ with regions. The RAS scheme underestimates the amplitudes over southeastern China, while the KF2 generates positive biases. The involving of the scale selective bias correction (SSBC) method can properly improve the simulated mean precipitation and diurnal cycle of summer precipitation. However, it shows lower skill in improving extreme precipitation indices over eastern China, especially in the experiments with CLD3 scheme. In summary, the selection of CLD1 and KF2 scheme, involving SSBC method performs better than the other experiments.

Effective control parameters in a deep convection scheme for improved simulation of the Madden–Julian oscillation

This work seeks to find the most effective parameters in a deep convection scheme (relaxed Arakawa–Schubert scheme) of the National Centers of Environmental Prediction Climate Forecast System model for improved simulation of the Madden–Julian Oscillation (MJO). A suite of sensitivity experiments are performed by changing physical components such as the relaxation parameter of mass flux for adjustment of the environment, the evaporation rate from large-scale precipitation, the moisture trigger threshold using relative humidity of the boundary layer, and the fraction of re-evaporation of convective (subgrid-scale) rainfall. Among them, the last two parameters are found to produce a significant improvement. Increasing the strength of these two parameters reduces light rainfall that inhibits complete formation of the tropical convective system or supplies more moisture that help increase a potential energy to large-scale environment in the lower troposphere (especially at 700 hPa), leading to moisture preconditioning favorable for further development and eastward propagation of the MJO. In a more humid environment, more organized MJO structure (i.e., space–time spectral signal, eastward propagation, and tilted vertical structure) is produced.

Inclusion of Linearized Moist Physics in NASA’s Goddard Earth Observing System Data Assimilation Tools

Abstract Inclusion of moist physics in the linearized version of a weather forecast model is beneficial in terms of variational data assimilation. Further, it improves the capability of important tools, such as adjoint-based observation impacts and sensitivity studies. A linearized version of the relaxed Arakawa–Schubert (RAS) convection scheme has been developed and tested in NASA’s Goddard Earth Observing System data assimilation tools. A previous study of the RAS scheme showed it to exhibit reasonable linearity and stability. This motivates the development of a linearization of a near-exact version of the RAS scheme. Linearized large-scale condensation is included through simple conversion of supersaturation into precipitation. The linearization of moist physics is validated against the full nonlinear model for 6- and 24-h intervals, relevant to variational data assimilation and observation impacts, respectively. For a small number of profiles, sudden large growth in the perturbation trajectory is encountered. Efficient filtering of these profiles is achieved by diagnosis of steep gradients in a reduced version of the operator of the tangent linear model. With filtering turned on, the inclusion of linearized moist physics increases the correlation between the nonlinear perturbation trajectory and the linear approximation of the perturbation trajectory. A month-long observation impact experiment is performed and the effect of including moist physics on the impacts is discussed. Impacts from moist-sensitive instruments and channels are increased. The effect of including moist physics is examined for adjoint sensitivity studies. A case study examining an intensifying Northern Hemisphere Atlantic storm is presented. The results show a significant sensitivity with respect to moisture.

Catastrophe-Concept-Based Cumulus Parameterization: Correction of Systematic Errors in the Precipitation Diurnal Cycle over Land in a GCM

Abstract The onset of cumulus convection in a grid column is a catastrophe, also known as a subcritical instability. Accordingly, in designing a cumulus parameterization scheme the onset of cumulus convection requires that a parameter crosses a critical value and the termination of cumulus convection requires that the same or a different parameter crosses a different critical value. Once begun, cumulus convection continues to exist, regardless of whether the onset criterion is still met, until the termination criterion is met. Also, the intensity of cumulus precipitation is related to how far the state is from the termination, not the onset, criterion. The cumulus parameterization schemes currently in use in GCMs, however, treat the onset of cumulus convection as a supercritical instability; namely, convection is turned on when a parameter exceeds a critical value and is turned off when the same parameter falls below the same critical value. Also, the intensity of cumulus precipitation is related to how far this critical value has been exceeded. Among the adverse consequences of the supercritical-instability-concept-based cumulus parameterization schemes are that over relatively flat land the precipitation peak occurs around noon—4–6 h too soon—and that the amplitude of the precipitation diurnal cycle is too weak. Based on the above-mentioned concept, a new cumulus parameterization scheme was designed by taking advantage of the existing infrastructure of the relaxed Arakawa–Schubert scheme (RAS), but replacing RAS's guiding principle with the catastrophe concept. Test results using NASA's Goddard Earth Observing System GCM, version 5 (GEOS-5), show dramatic improvement in the phase and amplitude of the precipitation diurnal cycle over relatively flat land.

Using Jacobian sensitivities to assess a linearization of the relaxed Arakawa–Schubert convection scheme

AbstractThe inclusion of linearized moist physics can increase the accuracy of 4D‐Var data assimilation and adjoint‐based sensitivity analysis. Moist processes such as convection can exhibit nonlinear behaviour. As a result, representation of these processes in a linear way requires much care; a straightforward linearization may yield a poor approximation to the behaviour of perturbations of interest and could contain numerical instability. Here, an extensive numerical study of the Jacobian of the relaxed Arakawa–Schubert (RAS) convection scheme is shown. A Jacobian based on perturbations at individual model levels can be used to understand the physical behaviour of the RAS scheme, predict how sensitive that behaviour is to the prognostic variables and determine the stability of a linearization of the scheme. The linearity of the scheme is also considered by making structured perturbations, constructed from the principle components of the model variables. Based on the behaviour of the Jacobian operator and the results when using structured perturbations, a suitable method for linearizing the RAS scheme is determined. For deep, strong convection, the structures of the RAS Jacobian are reasonably simple, the rate at which finite‐amplitude estimates of the structures change with respect to input perturbations is small and the eigenmodes of the Jacobian are not prohibitively unstable. For deep convection, an exact linearization is therefore suitable. For shallow convection, the RAS scheme can be more sensitive to the input prognostic variables due to the faster time‐scales and proximity to switches. Linearization of the RAS therefore requires some simplifications to smooth the behaviour for shallow convection. It is noted that the physical understanding of the scheme gained from examining the Jacobian provides a useful tool to the developers of nonlinear physical parametrizations.

Precipitation in Boreal Summer Simulated by a GCM with Two Convective Parameterization Schemes: Implications of the Intraseasonal Oscillation for Dynamic Seasonal Prediction

Abstract In this paper, the intraseasonal oscillation (ISO) and its possible link to dynamical seasonal predictability within a general circulation model framework is investigated. Two experiments with different convection scheme algorithms, namely, the simplified Arakawa–Schubert (SAS) and the relaxed Arakawa–Schubert (RAS) convection algorithms, were designed to compare seasonal simulations from 1979 to 2002 on a seasonal model intercomparison project (SMIP)-type simulation test bed. Furthermore, the wave characteristics (wave intensity, period, and propagation) of the simulated ISO signal provided by the model with two different convection schemes for extended boreal summers from 1997 to 2004 were compared to the observational ISO signal. Precipitation in the boreal summer was fairly well simulated by the model irrespective of the convection scheme used, but the RAS run outperformed the SAS run with respect to tabulated skill scores. Decomposition of the interannual variability of boreal summer precipitation based on observations and model results demonstrates that the seasonal predictability of precipitation is dominated by the intraseasonal component over the warm pool area and the SST-forced signal over the equatorial Pacific Ocean, implying that the seasonal mean anomalies are more predictable under active ISO conditions as well as strong ENSO conditions. Comparison of the ISO simulations with the observations revealed that the main features, such as the intensity of precipitation variance in the intraseasonal time scale and the evolution of propagating ISOs, were reproduced fairly well by the model; however, the wave characteristics associated with the ISO signals were better captured by the experiment with the RAS scheme than the SAS scheme. This study further suggests that accurate simulation of the ISO can improve the seasonal predictability of dynamical seasonal prediction systems.

Improved Forecasts of the Diurnal Cycle in the Tropics Using Multiple Global Models. Part I: Precipitation

Abstract The Tropical Rainfall Measuring Mission (TRMM) satellite supplemented with the Defense Meteorological Satellites Program (DMSP) microwave dataset provides accurate rain-rate estimates. Furthermore, infrared radiances from the geostationary satellites provide the possibility for mapping the diurnal change of tropical rainfall. Modeling of the phase and amplitude of the tropical rainfall is the theme of this paper. The present study utilizes a suite of global multimodels that are identical in all respects except for their cumulus parameterization algorithms. Six different cumulus parameterizations are tested in this study. These include the Florida State University (FSU) Modified Kuo Scheme (KUO), Goddard Space Flight Center (GSFC) Relaxed Arakawa–Schubert Scheme (RAS1), Naval Research Laboratory–Navy Operational Global Atmospheric Prediction System (NRL–NOGAPS) Relaxed Arakawa–Schubert Scheme (RAS2), NCEP Simplified Arakawa–Schubert Scheme (SAS), NCAR Zhang–McFarlane Scheme (ZM), and NRL–NOGAPS Emanuel Scheme (ECS). The authors carried out nearly 600 experiments with these six versions of the T170 Florida State University global spectral model. These are 5-day NWP experiments where the diurnal change datasets were archived at 3-hourly intervals. This study includes the estimation of skills of the phase and amplitudes of the diurnal rain using these member models, their ensemble mean, a multimodel superensemble, and those from a single unified model. Test results are presented for the global tropics and for some specific regions where the member models show difficulty in predicting the diurnal change of rainfall. The main contribution is the considerable improvement of the modeling of diurnal rain by deploying a multimodel superensemble and by constructing a single unified model. The authors also present a comparison of these findings on the modeling of diurnal rain from another suite of multimodels that utilized different versions of cloud radiation algorithms (instead of different cumulus parameterization schemes) toward defining the suite of multimodels. The principal result is that the superensemble does provide a future forecast for the total daily rain and for the diurnal change of rain through day 5 that is superior to forecasts provided by the best model. The training of the superensemble with good observed estimates of rain, such as those from TRMM, is necessary for such forecasts.

Sensitivity of the simulated East Asian summer monsoon climatology to four convective parameterization schemes

This study attempts to clarify the effects of parameterized convection on a simulated East Asian summer monsoon climatology from 1997 to 2006 within a regional climate model (RCM) framework. Four different convective parameterized schemes (CPSs) were chosen in the National Centers for the Environmental Prediction regional spectral model, the Simplified Arakawa‐Schubert (SAS), Relaxed Arakawa‐Schubert (RAS), NCAR Community Climate Model version 3 (CCM), and new Kain‐Fritsch (KF2) schemes. On the whole, there is no single scheme that outperforms the other in all aspects of the simulated climatology. The results show that the SAS and KF2 schemes are capable of reproducing the 10‐year June–July–August climatology with a certain wet bias over land and dry bias over the oceans. The SAS scheme is capable of resolving the interannual variations of the monsoon precipitation, and the KF2 is able to capture the intraseasonal variation. The RAS scheme significantly reduces precipitation over land compared to other schemes, but interannual variabilities are reasonably reproduced. On the contrary, the CCM scheme significantly overestimates the precipitation over land as well as ocean. Discernable differences among four CPSs are found in the distribution of the spatial spectrum, in which the KF2 scheme is the most effective in adding regional details to an external large‐scale forcing. The feasibility of a physics ensemble using different convection schemes and the impacts of domain size are also discussed.

Simulation of 2006 monsoon using T170L42 AGCM: sensitivity to convective parameterization schemes

AbstractIn this study we used the National Center for Environmental Prediction (NCEP) T170L42 Global Forecast System model for simulating the monsoon of 2006 using two different cumulus parameterization schemes viz. the Simple Arakawa–Schubert (SAS) scheme and the Relaxed Arakawa–Schubert (RAS) scheme. The NCEP Coupled Forecast System (CFS) monthly forecast sea surface temperatures (SST) were used for simulating the monsoon season. It is seen that both the schemes forecast the mean seasonal rainfall close to the observed. However, there were differences in the spatial and temporal distribution of the rainfall. The spatial distribution of the precipitation simulated by the RAS scheme was comparable to the observed. The SAS scheme simulated realistic distribution of the rainfall in the months of June and July. In the months of August and September, the SAS scheme could not simulate the convective regions over the south and central Bay of Bengal, Arabian Sea and the Indian landmass. The SAS scheme simulated withdrawal‐like symptoms of the monsoon in the month of August itself. However, the same SAS scheme simulated more realistic rainfall distribution over the Bay of Bengal when the model was run with climatological SST and also when the model was run at a resolution of T62 and with CFS‐forecast SST. The onset of the monsoon over the Kerala coast of India simulated with both the schemes was within one pentad of the observed date of onset. Copyright © 2008 Royal Meteorological Society

Parameterization of aerosol indirect effect to complement McRAS cloud scheme and its evaluation with the 3-year ARM-SGP analyzed data for single column models

Microphysics of clouds with the Relaxed Arakawa–Schubert Scheme (McRAS) was upgraded for simulating the Aerosol Indirect Effects (AIE) for water clouds. The AIE comprises of i) Fountoukis and Nenes aerosol activation module for obtaining cloud condensation nuclei; ii) Seifert and Beheng algorithms for precipitation microphysics but with modified accretion constant for the coarse vertical-resolution typical of a global general circulation model (GCM); and iii) Khvorostyanov and Curry parameterization for computing the effective radius ( r e ) of cloud drops. The upgraded package, named McRAS-AC, was evaluated using the 3-year ARM-SGP Single Column Model (SCM) data. Invoking only the most dominant sulfate aerosols over the region, McRAS-AC simulated realistic annual mean and annual cycles of cloud water, cloud optical thicknesses, cloud drop number concentration, and r e . The follow-on SCM-sensitivity simulations showed that accretion of cloud water is sensitive to i) the terminal velocity of hydrometeors produced by autoconversion and ii) cloud height increases due to in-cloud condensation heating. The impact of aerosol mass concentration on the resultant column cloud water, and bulk optical properties of clouds were assessed by using 1/8 to 8 times the average monthly aerosol mass concentration estimates of GOCART aerosol climatology. A log-linear relation between cloud-radiative forcing and aerosol-mass concentration emerged in the simulated data.

Evaluation of RSM-Simulated Precipitation During CEOP

Precipitation simulated using the Regional Spectral Model (RSM) during the Coordinated Enhanced Observing Period (CEOP; July 1, 2001 to December 31, 2004) is evaluated by transferring the RSM to seven different regions of the globe and comparing the simulations with observations. These regions cover the eight Continental-Scale Experiments (CSEs) of the Global Energy and Water-cycle EXperiment (GEWEX) and encompass a broad variety of physical and dynamical meteorological processes. Gridded observations of the Global Precipitation Climatology Project (GPCP) and the Global Precipitation Climatology Center (GPCC), as well as CEOP reference site precipitation observations are compared with the RSM simulated precipitation for the first half of the CEOP Enhanced Observation Period (EOP) III (October 2002 to March 2003). After estimating the uncertainty ranges of both the model and the observations, model deficiencies were obtained for almost all model domains in terms of the amount of simulated precipitation. Although the RSM is able to accurately simulate the seasonal evolution and spatial distribution of precipitation, the RSM has an almost uniform positive bias (i.e., RSM values are greater than observed values) over almost all the domains. Most of the positive bias is associated with convection in the Intertropical Convergence Zone (ITCZ) or monsoonal convection in Southeast Asia. Predicted stratiform precipitation is also excessive over areas ofelevated topography. As the control simulations used a Relaxed Arakawa-Schubert scheme (RAS), sensitivity tests with three additional convection schemes were then carried out to assess whether the simulations could be improved. The additional convection schemes were: 1) the Simplified Arakawa-Schubert scheme (SAS); 2) the Kain-Fritsch scheme (KF); and 3) the National Centers for Atmospheric Research (NCAR) Community Climate Model (CCM) scheme. The precipitation simulation was significantly improved for almost all domains when using either the KF scheme or the SAS scheme. The best simulations of ITCZ convective precipitation and Southeast Asian monsoon convective precipitation were achieved using the SAS convection scheme.

Recent Modifications of the Emanuel Convective Scheme in the Navy Operational Global Atmospheric Prediction System

Abstract The convective parameterization of Emanuel has been employed in the forecast model of the Navy Operational Global Atmospheric Prediction System (NOGAPS) since 2000, when it replaced a version of the relaxed Arakawa–Schubert scheme. Although in long-period data assimilation forecast tests the Emanuel scheme has been found to perform quite well in NOGAPS, particularly for tropical cyclones, some weaknesses have also become apparent. These weaknesses include underprediction of heavy-precipitation events, too much light precipitation, and unrealistic heating at upper levels. Recent research efforts have resulted in modifications of the scheme that are designed to reduce such problems. One change described here involves the partitioning of the cloud-base mass flux into mixing cloud mass flux at individual levels. The new treatment significantly reduces a heating anomaly near the tropopause that is associated with a large amount of mixing cloud mass flux ascribed to that region in the original Emanuel ...

Comprehensive test of different cumulus parameterization schemes for the simulation of the Indian summer monsoon

The global spectral model of NCMRWF at T80 horizontal resolution and 18 vertical levels has been integrated for the summer season (July) using different cumulus parameterization schemes namely, the Simplified Arakawa-Schubert scheme (SAS), the Relaxed Arakawa-Schubert Scheme (RAS), and the Kuo-type cumulus parameterization scheme (KUO). The results have been compared with mean analysis of the operational NCMRWF model (ANA) and other available observations. Results indicate that, while the global distributions of basic fields such as the wind, temperature and moisture are fairly well simulated by all the three schemes, there are many differences seen in the simulation of the typical features of the Indian summer monsoon. The strength of the Low Level Westerly Jet (LLWJ), the Cross Equatorial Flow (CEF), and the Tropical Easterly Jet (TEJ) are better simulated by RAS and SAS as compared to ANA than the KUO scheme. RAS and SAS produce strong rising motion owing to strong intensity of convection produced by these two schemes. This in turn produces stronger Hadley cell by RAS and SAS than compared to the KUO scheme. Simulation of the 200 mb velocity potential and divergent wind by RAS and SAS produced two prominent centers, one in the Bay of Bengal and another in the Western Pacific, which correspond to the intense latent heating by cumulus convection during the active monsoon phase. The velocity potential and divergent winds were weaker in KUO, than compared to RAS and SAS. The simulation of OLR is improved by RAS as compared to observations. The cold bias produced by KUO at 200 mb is reduced by RAS and is substantially improved by SAS. Study of observed and simulated rainfall indicated that RAS and SAS produced better distribution of precipitation over the Western Ghat Mountains and the Arakan coast, where deep cumulus convection is produced due to orographic forcing of the warm moist air. The KUO scheme underestimated the rainfall over these two regions, but produced slightly better distribution of rainfall over the northwest and central India, where the intensity of convection is relatively weaker. Evaluation of overall dynamics, thermal structure and rainfall indicates that in general, SAS is able to provide relatively better results compared to other two schemes.

Sensitivity of tropical storms simulated by a general circulation model to changes in cumulus parametrization

AbstractA number of recent studies have examined the statistics of tropical storms simulated by general circulation models (GCMs) forced by observed sea surface temperatures. Many GCMs have demonstrated an ability to simulate some aspects of the observed interannual variability of tropical storms, in particular, variability in storm frequency. This has led to nascent attempts to use GCMs as part of programs to produce operational seasonal forecasts of tropical‐storm numbers.In this study, the sensitivity of the statistics of GCM‐simulated tropical storms to changes in the model's physical parametrizations is examined. After preliminary results indicated that these statistics were most sensitive to details of the convective parametrization, GCM simulations with identical dynamical cores but different convective parametrizations were created. The parametrizations examined included moist convective adjustment, two variants of the Arakawa‐Schubert scheme, and several variants of the relaxed Arakawa‐Schubert (RAS) scheme; the impact of including a shallow‐convection parametrization was also examined.The simulated tropical‐storm frequency, intensity, structure, and interannual variability were all found to exhibit significant sensitivities to changes in convective parametrization. A particularly large sensitivity was found when the RAS and Arakawa‐Schubert parametrizations were modified to place restrictions on the production of deep convection.Climatologies of the GCM tropical atmosphere and composites of tropical storms were examined to address the question of whether the tropical‐storm statistics were directly impacted on by changes in convection associated with tropical storms, or if they were indirectly affected by parametrization‐induced changes in the tropical mean atmosphere. A number of results point to the latter being the primary cause. A regional hurricane model, initialized with mean states from the GCM simulation climatologies, is used to further investigate this point. Particularly compelling is the fact that versions of the RAS scheme that produce significantly less realistic simulations of tropical storms nevertheless produce a much more realistic interannual variability of storms, apparently due to an improved tropical mean climate.A careful analysis of the background convective available potential energy (CAPE) is used to suggest that this quantity is particularly relevant to the occurrence of tropical storms in the low‐resolution GCMs, although this may not be the case with observations. If the tropical CAPE is too low, tropical storms in the low‐resolution GCMs cannot form with realistic frequency.

Microphysics of Clouds with the Relaxed Arakawa–Schubert Scheme (McRAS). Part I: Design and Evaluation with GATE Phase III Data

Abstract A prognostic cloud scheme named McRAS (Microphysics of Clouds with Relaxed Arakawa–Schubert Scheme) has been designed and developed with the aim of improving moist processes, microphysics of clouds, and cloud–radiation interactions in GCMs. McRAS distinguishes three types of clouds: convective, stratiform, and boundary layer. The convective clouds transform and merge into stratiform clouds on an hourly timescale, while the boundary layer clouds merge into the stratiform clouds instantly. The cloud condensate converts into precipitation following the autoconversion equations of Sundqvist that contain a parametric adaptation for the Bergeron–Findeisen process of ice crystal growth and collection of cloud condensate by precipitation. All clouds convect, advect, as well as diffuse both horizontally and vertically with a fully interactive cloud microphysics throughout the life cycle of the cloud, while the optical properties of clouds are derived from the statistical distribution of hydrometeors and i...

Microphysics of Clouds with the Relaxed Arakawa–Schubert Scheme (McRAS). Part II: Implementation and Performance in GEOS II GCM

Abstract A prognostic cloud scheme named the Microphysics of Clouds with the Relaxed Arakawa–Schubert Scheme (McRAS) and the Simple Biosphere Model have been implemented in a version of the Goddard Earth Observing System (GEOS) II GCM at a 4° latitude × 5° longitude × 20 sigma-layer resolution. The McRAS GCM was integrated for 50 months. The integration was initialized with the European Centre for Medium-Range Weather Forecasts analysis of observations for 1 January 1987 and was forced with the observed sea surface temperatures and sea-ice distribution; on land, the permanent ice and vegetation properties (biomes and soils) were climatological, while the soil moisture and snow cover were prognostic. The simulation shows that the McRAS GCM yields realistic structures of in-cloud water and ice, and cloud-radiative forcing (CRF) even though the cloudiness has some discernible systematic errors. The simulated intertropical convergence zone (ITCZ) has a realistic time mean structure and seasonal cycle. The sim...

台風の数値予報に対する非断熱初期値化および積雲パラメタリゼーションの効果

Numerical experiments were conducted with a regional atmospheric model to investigate the suitability of the model for simulation/prediction of tropical cyclones (TCs). The model uses primitive equations and is similar in construction to a regional atmospheric model, called RegCM, which has been used extensively for regional climate modeling. The suitability of the model for TC study was tested in the mode of short-range forecasts to find out how well the model can reproduce TC behaviors with a special attention on their genesis and development. Objective analysis data for typhoons Ed (9018) and Flo (9019) in September 1990 were used as the input data. In addition, observed precipitation (PR) rates estimated from hourly infrared satellite measurements were used. In the prediction experiments, we focused on two aspects: One was to study the impact of data initialization. The other was to examine the sensitivity of forecast depending on the choice of two cumulus parameterizations, Kuo and relaxed Arakawa-Schubert (RAS) schemes. The initialization to the input data was done through the combination of diabatic nonlinear normal mode initialization for dynamical fields and cumulus initialization for moisture. The diabatic heating rate was determined from radiative and condensation heating rates using the input data, including observed PR rates. The initialization of moisture was done through the inversion of cumulus scheme for a specified PR rate. Positive impacts of the initialization on reproducing the behaviors of both typhoons are clearly demonstrated in the use of both cumulus schemes. In particular, the initialization results in successful simulations of initial PR field without spinup problems. Thus, the positive impact is greatest in the case of TC genesis. The reproducibility of PR by the model with RAS scheme is superior, and the RAS scheme appears more suitable than the Kuo scheme for the intensity prediction of developing typhoons. However, the use of the Kuo scheme produces better scores in mean displacement errors.

Variational Assimilation of Precipitation Data Using Moist Convective Parameterization Schemes: A 1D-Var Study

Some basic aspects related to the problem of incorporating moist convective processes in a variational data assimilation framework are considered. The methodology is based on inverse problem theory and is formulated in its simplest context where the adjustment of temperature and humidity fields take place only in the vertical. In contrast to previous studies on the subject, the impact of error statistics from prior information and data sources of information is clarified. The accuracy of linearization of convection operators and the resulting impact in a minimization procedure are examined. The former was investigated using Monte Carlo methods. Versions of two schemes are examined: the Kuo–Anthes scheme and the relaxed Arakawa–Schubert scheme (RAS). It is found, in general, that for nonpathological convective points (i.e., points where convection always remains active during the minimization process), a significant adjustment of convection (and precipitation rate) is realizable within the range of realistic background temperature and specific humidity errors and precipitation rate observation errors. Typically, three to five iterations are sufficient for convergence of the variational algorithm for both convective schemes. The degree of nonlinearity of both schemes appears comparable. The vertical correlation length for the background error temperature field is shown to produce a strong interaction with the RAS scheme in the minimization process where significantly different vertical structures of analysis increments for the temperature field are generated in the vicinity of a critical value of the correlation length.