Dependence of Hurricane Intensity and Structures on Vertical Resolution and Time-Step Size

In view of the growing interests in the explicit modeling of clouds and precipitation, the effects of varying vertical resolution and time-step sizes on the 72-h explicit simulation of Hurricane Andrew (1992) are studied using the Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) mesoscale model (i.e., MM5) with the finest grid size of 6 km. It is shown that changing vertical resolution and time-step size has significant effects on hurricane intensity and inner-core cloud/precipitation, but little impact on the hurricane track. In general, increasing vertical resolution tends to produce a deeper storm with lower central pressure and stronger three-dimensional winds, and more precipitation. Similar effects, but to a less extent, occur when the time-step size is reduced. It is found that increasing the low-level vertical resolution is more efficient in intensifying a hurricane, whereas changing the upper-level vertical resolution has little impact on the hurricane intensity. Moreover, the use of a thicker surface layer tends to produce higher maximum surface winds. It is concluded that the use of higher vertical resolution, a thin surface layer, and smaller time-step sizes, along with higher horizontal resolution, is desirable to model more realistically the intensity and inner-core structures and evolution of tropical storms as well as the other convectively driven weather systems.

Effects of adjusting vertical resolution on the eastern equatorial Pacific cold tongue

The vertical resolution of LICOM1.0 (LASG/IAP Climate System Ocean Model, version 1.0) is adjusted by increasing the level amount within the upper 150 m while keeping the total of levels. It is found that the eastern equatorial Pacific cold tongue is sensitive to the adjustment. Compared with the simulation of the original level scheme, the adjusting yields a more realistic structure of cold tongue extending from the coast of Peru to the equator, as well as a temperature minimum at Costa Rica coast, north of the cold tongue. In the original scheme experiment, the sharp heating by net surface heat flux at the beginning of spin-up leads to a great warm- ing in the eastern equatorial Pacific Ocean. The weak vertical advection due to a too thick mixed layer in the coarse vertical structure also accounts for the warm bias. The fact that most significant improvements of the upper 50 m temperature appear at the region of the thinnest mixed layer indicates the necessity of fine vertical resolution for the eastern equatorial Pacific Ocean. However, the westward extension of equatorial cold tongue, a defect in the original scheme, gets even more serious in the adjusting scheme due to the intensi- fied vertical velocity and hence vertical advection in the central-eastern equatorial Pacific Ocean.

Improved Tropical Cyclone Forecasts with Increased Vertical Resolution in the TRAMS Model

The numerical simulation of typhoons has been found to be very sensitive to the vertical resolution of the model.During the updating of the TRAMS model from version 1.0 to 3.0,the horizontal resolution has been increased from 36 km to 9 km,while the vertical layer number only increased from 55 to 65 layers.The lack of high vertical resolution limits the performance of the TRAMS model in typhoon forecasting to a certain extent.In order to study the potential improvement of typhoon forecasting by increasing the vertical resolution,this paper increases the vertical resolution of the TRAMS model from 65 to 125 layers for the first time for a comparative simulation test.The results of the case study with Typhoon Hato(2017)show that the model with high vertical resolution can significantly enhance the warm structure caused by water vapor flux convergence and vertical transport,thus accurately simulating the rapid strengthening process of the typhoon.Meanwhile,the model with 125-layer vertical resolution can simulate the asymmetric structural characteristics of the wind field,which are closer to the observations and can help to reduce the bias in typhoon track forecasting.The improvement of vertical resolution is also trialed by using the batch test results of several landfalling typhoons in 2016-2017.The experimental results show that the typhoon forecast of the model becomes consistent with the observations only when the number of vertical layers of the model increases to about 125 layers,which in turn causes a large computational burden.In the next step,we will try to solve the computational burden problem caused by ultra-high vertical resolution with the top boundary nesting technique,and realize the application of high vertical resolution in the actual operation of the TRAMS model.

IMPACT OF VERTICAL RESOLUTION, MODEL TOP AND DATA ASSIMILATION ON WEATHER FORECASTING——A CASE STUDY

The impacts of stratospheric initial conditions and vertical resolution on the stratosphere by raising the model top,refining the vertical resolution,and the assimilation of operationally available observations,including conventional and satellite observations,on continental U.S.winter short-range weather forecasting,were investigated in this study.The initial and predicted wind and temperature profiles were analyzed against conventional observations.Generally,the initial wind and temperature bias profiles were better adjusted when a higher model top and refined vertical resolution were used.Negative impacts were also observed in both the initial wind and temperature profiles,over the lower troposphere.Different from the results by only raising the model top,the assimilation of operationally available observations led to significant improvements in both the troposphere and stratosphere initial conditions when a higher top was used.Predictions made with the adjusted stratospheric initial conditions and refined vertical resolutions showed generally better forecasting skill.The major improvements caused by raising the model top with refined vertical resolution,as well as those caused by data assimilation,were in both cases located in the tropopause and lower stratosphere.Negative impacts were also observed in the predicted near surface wind and lower-tropospheric temperature.These negative impacts were related to the uncertainties caused by more stratospheric information,as well as to some physical processes.A case study shows that when we raise the model top,put more vertical layers in stratosphere and apply data assimilation,the precipitation scores can be slightly improved.However,more analysis is needed due to uncertainties brought by data assimilation.

Impacts of Horizontal and Vertical Resolutions on the Microphysical Structure and Boundary Layer Fluxes of Typhoon Hato(2017)

We set four sets of simulation experiments to explore the impacts of horizontal resolution(HR)and vertical resolution(VR)on the microphysical structure and boundary layer fluxes of tropical cyclone(TC)Hato(2017).The study shows that higher HR tends to strengthen TC.Increasing VR in the upper layers tends to weaken TC,while increasing VR in the lower layers tends to strengthen TC.Simulated amounts of all hydrometeors were larger with higher HR.Increasing VR at the upper level enhanced the mixing ratios of cloud ice and cloud snow,while increasing VR at the lower level elevated the mixing ratios of graupel and rainwater.HR has greater impact on the distributions of hydrometeors.Higher HR has a more complete ring structure of the eyewall and more concentrated hydrometeors along the cloud wall.Increasing VR at the lower level has little impact on the distribution of TC hydrometeors,while increasing VR at the upper level enhances the cloud thickness of the eyewall area.Surface latent heat flux(SLHF)is influenced greatly by resolution.Higher HR leads to larger water vapor fluxes and larger latent heat,which would result in a stronger TC.A large amount of false latent heat was generated when HR was too high,leading to an extremely strong TC,VR has a smaller impact on SLHF than HR.But increasing VR at the upper-level reduces the SLHF and weakens TC,and elevating VR at the lower-level increases the SLHF and strengthens TC.The changes in surface water vapor flux and SLHF were practically identical and the simulation results were improved when HR and VR were more coordinated.The friction velocity was greater with higher VR.Enhancing VR at the lower level increased the friction velocity,while increasing VR at the upper level reduced it.

The impact of vertical resolution on the simulation of Typhoon Lekima (2019) by a cloud-permitting model

The impact of vertical resolution on the simulation of Typhoon Lekima(2019)is investigated using the Weather Research and Forecasting(WRF)model version 3.8.1.Results show that decreasing vertical grid spacing from approximately 1000 m to 100 m above 1 km height barely influences the simulated track.However,significant differences are found in the simulated tropical cyclone(TC)structure.The simulation with the coarsest vertical resolution shows a clear double warm-core structure.The upper warm core weakens and even disappears with the increase of vertical resolution.A broader eye and a more slantwise eyewall are observed with the increase of vertical resolution due to the vertically extended lower-level and upper-level outflow,which likely results in a weaker subsidence.Vertical grid convergence is evaluated with the simulated kinetic energy(KE)spectra.As the vertical grid spacing becomes finer than 200 m,convergent KE spectra are found in both the free atmosphere and the outer core of the TC.However,sensitivity tests reveal that the grid convergence is sensitive to the choice of the planetary boundary layer scheme.

A performance evaluation of remotely sensed sea surface salinity products in combination with other surface measurements in reconstructing three-dimensional salinity fields

Several remotely sensed sea surface salinity（SSS） retrievals with various resolutions from the soil moisture and ocean salinity（SMOS） and Aquarius/SAC-D missions are applied as inputs for retrieving salinity profiles（S） using multilinear regressions. The performance is evaluated using a total root mean square（RMS） error, different error sources, and the feature resolutions of the retrieved S fields. In the mixed layer of the salinity, the SSS-S regression coefficients are uniformly large. The SSS inputs yield smaller RMS errors in the retrieved S with respect to Argo profiles as their spatial or temporal resolution decreases. The projected SSS errors are dominant, and the retrieved S values are more accurate than those of climatology in the tropics except for the tropical Atlantic, where the regression errors are abnormally large. Below that level, because of the influence of a sea level anomaly, the areas of high-accuracy S values shift to higher latitudes except in the high-latitude southern oceans, where the projected SSS errors are abnormally large. A spectral analysis suggests that the CATDS-0.25° results are much noisier and that the BEC-L4-0.25° results are much smoother than those of the other retrievals. Aquarius-CAP-1° generates the smallest RMS errors, and Aquarius-V2-1° performs well in depicting large-scale phenomena. BEC-L3-0.25°,which has small RMS errors and remarkable mesoscale energy, is the best fit for portraying mesoscale features in the SSS and retrieved S fields. The current priority for retrieving S is to improve the reliability of satellite SSS especially at middle and high latitudes, by developing advanced algorithms, combining both sensors, or weighing between accuracy and resolutions.

The research on method of interlayer modeling based on seismic inversion and petrophysical facies

Currently,the three-dimensional distribution of interlayer is realized by stochastic modeling.Traditionally,the three-dimensional geological modeling controlled by sedimentary facies models is built on the basis of logging interpretation parameters and geophysical information.Because of shallow gas-cap,the quality of three-dimensional seismic data vertical resolution in research area cannot meet the interlayer research that is below ten meters.Moreover,sedimentary facies cannot commendably reveal interlayer distribution and the well density is very sparse in research area.So,it is difficult for conventional technology to finely describe interlayers.In this document,it uses L1-L2 combined norm constrained inversion to enhance the recognition capability of interlayer in seismic profile and improve the signal to noise ratio,the wave group characteristics and the vertical resolution of three-dimensional data and classifies petrophysical facies of interlayer based on core,sedimentary facies and logging interpretation.The interlayer model which is based on seismic inversion model and petrophysical facies can precisely simulate the distribution of reservoir and interlayer.The results show that the simulation results of this new methodology are consistent with the dynamic production perfectly which provide a better basis for producing and mining remaining oil and a new interlayer modeling method for sparse well density.