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Xu Zhang, Jian-Wen Bao, Baode Chen, and Wei Huang

Abstract

Coarse-grained results from a large-eddy simulation (LES) using the Weather Research and Forecasting (WRF) Model were compared in this study with the WRF simulations at a typical convection-permitting horizontal grid spacing of 3 km for an idealized case of deep moist convection. The purpose of this comparison is to identify major differences at the subgrid process level between two widely used deep convection parameterization schemes in the WRF Model. It is shown that there are considerable differences in subgrid process representations between the two schemes due to different parameterization formulations and underlying assumptions. The two schemes not only differ in trigger function, subgrid cloud model, and closure assumptions but also disagree with the coarse-grained LES results in terms of vertical mass flux profiles. Thus, it is difficult to discern which scheme is more advantageous over the other at the subgrid process level. The conclusions from this study highlight the importance of establishing benchmarks using observations and LES to develop and evaluate convection parameterization schemes suitable for models at convection-permitting resolution.

Open access
Milija Zupanski

Abstract

A new method for ensemble data assimilation that incorporates state space covariance localization, global numerical optimization, and implied Bayesian inference is presented. The method is referred to as the MLEF with state space localization (MLEF-SSL) due to its similarity with the maximum likelihood ensemble filter (MLEF). One of the novelties introduced in MLEF-SSL is the calculation of a reduced-rank localized forecast error covariance using random projection. The Hessian preconditioning is accomplished via Cholesky decomposition of the Hessian matrix, accompanied with solving triangular system of equations instead of directly inverting matrices. For ensemble update, the MLEF-SSL system employs resampling of posterior perturbations. The MLEF-SSL was applied to Lorenz model II and compared to ensemble Kalman filter with state space localization and to MLEF with observation space localization. The observations include linear and nonlinear observation operators, each applied to integrated and point observations. Results indicate improved performance of MLEF-SSL, particularly in assimilation of integrated nonlinear observations. Resampling of posterior perturbations for an ensemble update also indicates a satisfactory performance. Additional experiments were conducted to examine the sensitivity of the method to the rank of random matrix and to compare it to truncated eigenvectors of the localization matrix. The two methods are comparable in application to low-dimensional Lorenz model, except that the new method outperforms the truncated eigenvector method in case of severe rank reduction. The random basis method is simple to implement and may be more promising for realistic high-dimensional applications.

Open access
Joshua Chun Kwang Lee, Anurag Dipankar, and Xiang-Yu Huang

Abstract

The diurnal cycle is the most prominent mode of rainfall variability in the tropics, governed mainly by the strong solar heating and land–sea interactions that trigger convection. Over the western Maritime Continent, complex orographic and coastal effects can also play an important role. Weather and climate models often struggle to represent these physical processes, resulting in substantial model biases in simulations over the region. For numerical weather prediction, these biases manifest themselves in the initial conditions, leading to phase and amplitude errors in the diurnal cycle of precipitation. Using a tropical convective-scale data assimilation system, we assimilate 3-hourly radiosonde data from the pilot field campaign of the Years of Maritime Continent, in addition to existing available observations, to diagnose the model biases and assess the relative impacts of the additional wind, temperature, and moisture information on the simulated diurnal cycle of precipitation over the western coast of Sumatra. We show how assimilating such high-frequency in situ observations can improve the simulated diurnal cycle, verified against satellite-derived precipitation, radar-derived precipitation, and rain gauge data. The improvements are due to a better representation of the sea breeze and increased available moisture in the lowest 4 km prior to peak convection. Assimilating wind information alone was sufficient to improve the simulations. We also highlight how during the assimilation, certain multivariate background error constraints and moisture addition in an ad hoc manner can negatively impact the simulations. Other approaches should be explored to better exploit information from such high-frequency observations over this region.

Open access
Biao Geng and Masaki Katsumata

Abstract

In this study, we examined the variations of precipitation morphology and rainfall in relation to the simultaneous passages of a Madden–Julian oscillation (MJO) event and convectively coupled equatorial waves (CCEWs) observed during the Years of the Maritime Continent pilot study. We utilized globally merged infrared brightness temperature data and the radiosonde and radar data observed aboard the Research Vessel Mirai at 4°4′S, 101°54′E. As well as the observed MJO event, equatorial Rossby waves (ERWs), Kelvin waves (KWs), and mixed Rossby–gravity waves (MRGWs) were identified. The radar data exhibited high-frequency variation, mainly caused by KWs and MRGWs, and low-frequency variation, mainly caused by the MJO and ERWs. The MRGWs predominantly modulated convective echo areas and both convective and stratiform volumetric rainfall. In contrast, the MJO event had little influence on the variance of convective echoes. Moreover, stratiform echo areas and volumetric rainfall were more strongly modulated by the combined effects of the MJO, ERWs, KWs, and MRGWs than their convective counterparts. The intense development of stratiform echo areas and volumetric rainfall was coherent with the superimposition of the active phases of the MJO event and all the analyzed CCEWs. The strongest development and a significant reduction of convective echo-top heights before and after the peak MJO date, respectively, were coherent with the passages of ERWs and MRGWs, which were the dominant wave types in modulating echo-top heights. Thus, it appears that the superimposition of the CCEWs on the MJO event exerted complex modulations on the convective activities within the MJO event.

Open access
Yasutaka Ikuta, Masaki Satoh, Masahiro Sawada, Hiroshi Kusabiraki, and Takuji Kubota

Abstract

In this study, the single-moment 6-class bulk cloud microphysics scheme used in the operational numerical weather prediction system at the Japan Meteorological Agency was improved using the observations of the Global Precipitation Measurement (GPM) core satellite as reference values. The original cloud microphysics scheme has the following biases: underestimation of cloud ice compared to the brightness temperature of the GPM Microwave Imager (GMI) and underestimation of the lower troposphere rain compared to the reflectivity of GPM Dual-frequency Precipitation Radar (DPR). Furthermore, validation of the dual-frequency rate of reflectivity revealed that the dominant particles in the solid phase of simulation were graupel and deviated from DPR observation. The causes of these issues were investigated using a single-column kinematic model. The underestimation of cloud ice was caused by a high ice-to-snow conversion rate, and the underestimation of precipitation in the lower layers was caused by an excessive number of small-diameter rain particles. The parameterization of microphysics scheme is improved to eliminate the biases in the single-column model. In the forecast obtained using the improved scheme, the underestimation of cloud ice and rain is reduced. Consequently, the prediction errors of hydrometeors were reduced against the GPM satellite observations, and the atmospheric profiles and precipitation forecasts were improved.

Open access
Free access
Yuta Kawai and Hirofumi Tomita

Abstract

Recently, large-eddy simulation (LES) has been increasingly employed in meteorological simulations because it is a promising method for turbulent parameterization. However, it is still difficult to affirm that the numerical accuracy required for a dynamical core is fully understood. In this study, we derived two theoretical criteria for the order of accuracy of the advection term in a typical situation of the atmospheric boundary layer, and demonstrate their validity by numerical experiments. In the targeted grid-spacing of O(10) m, we determined the required order of accuracy as follows: Based on the criterion of the numerical diffusion error, the upwind scheme must have at least seventh-order accuracy. The fourth-order central scheme is barely acceptable with fourth-order explicit diffusion, provided that its coefficient is one or two orders of magnitude smaller than the implicit diffusion coefficient of the third-order upwind scheme. Based on the criterion of numerical dispersion error, at minimum, the seventh or eighth order is required. The dispersion error was indirect for the energy spectra, although we expect it may affect the local turbulence mechanism. We also investigated the effects of temporal discretization for compressible models, and found that relatively lower-order time schemes are available up to the O(10) m grid spacing if the time step is sufficiently small due to sound wave limitations. The importance of the derived criteria is that the required order of accuracy increases as the grid spacing decreases. This suggests that considerable care should be taken regarding the numerical error problem for future high-resolution LES.

Open access
Satoru Kasuga, Meiji Honda, Jinro Ukita, Shozo Yamane, Hiroaki Kawase, and Akira Yamazaki

Abstract

We propose a new scheme based on geopotential height fields to detect cutoff lows starting in the preexisting trough stage. The intensity and scale derived from the proposed scheme will allow for a better understanding of the cutoff low life cycle. These cutoff lows often accompany mesoscale disturbances, causing adverse weather-related events, such as intense torrential rainfall and/or tornadoes. The proposed scheme quantifies the geometric features of a depression from its horizontal height profile. The height slope of a line intersecting the depression bottom and the nearest tangential point (optimal slope) locally indicates the intensity and scale of an isolated depression. The strength of the proposed scheme is that, by removing a local background height slope from a geopotential height field, the cutoff low and its preexisting trough are seamlessly detected as an identical depression. The distribution maps for the detected cutoff lows and preexisting troughs are illustrated along with their intensities, sizes, and local background flows estimated from snapshot height fields. We conducted climatological comparisons of cutoff lows to determine the utility of the proposed scheme.

Open access
Erika L. Duran, Emily B. Berndt, and Patrick Duran

Abstract

Hyperspectral infrared satellite sounding retrievals are used to examine thermodynamic changes in the tropical cyclone (TC) environment associated with the diurnal cycle of radiation. Vertical profiles of temperature and moisture are retrieved from the Suomi National Polar–orbiting Partnership (S–NPP) satellite system, National Oceanic and Atmospheric Administration (NOAA)–20, and the Meteorological Operational (MetOp) A/B satellite system, leveraging both infrared and microwave sounding technologies. Vertical profiles are binned radially based on distance from the storm center and composited at 4–hr intervals to reveal the evolution of the diurnal cycle. For the three cases examined – Hurricane Dorian (2019), Hurricane Florence (2018) and Hurricane Irma (2017) – a marked diurnal signal is evident that extends through a deep layer of the troposphere. Statistically significant differences at the 95% level are observed in temperature, moisture, and lapse rate profiles, indicating a moistening and destabilization of the mid to upper troposphere that is more pronounced near the inner core of the TC at night. Observations support a favorable environment for the formation of deep convection caused by diurnal differences in radiative heating tendencies, which could partially explain why new diurnal pulses tend to form around sunset. These findings demonstrate that the diurnal cycle of radiation affects TC thermodynamics through a deep layer of the troposphere, and suggest that hyperspectral infrared satellite sounding retrievals are valuable assets in detecting thermodynamic variations in TCs.

Open access
Richard B. Bagley and Craig B. Clements

Abstract

The second largest fire shelter deployment in U.S. history occurred in August 2003 during the Devil Fire, which was burning in a remote and rugged region of the San Francisco Bay Area, when relative humidity abruptly dropped in the middle of the night, causing rapid fire growth. Nocturnal drying events in the higher elevations along California’s central coast are a unique phenomenon that poses a great risk to wildland firefighters. Single-digit relative humidity with dewpoints below −25°C is not uncommon during summer nights in this region. To provide the fire management community with knowledge of these hazardous conditions, an event criterion was established to develop a climatology of nocturnal drying and to investigate the synoptic patterns associated with these events. A lower-tropospheric source region of dry air was found over the northeastern Pacific Ocean corresponding to an area of maximum low-level divergence and associated subsidence. This dry air forms above a marine inversion and advects inland overnight with the marine layer and immerses higher-elevation terrain with warm and dry air. An average of 15–20 nocturnal drying events per year occur in elevations greater than 700 m in the San Francisco Bay Area, and their characteristics are highly variable, making them a challenge to forecast.

Open access