Mesoscale Model MM5 Research Articles

Numerical study of the spin‐up of a tropical low over land during the Australian monsoon

An analysis of numerical simulations of tropical low intensification over land is presented. The simulations are carried out using the MM5 mesoscale model with initial and boundary conditions provided by ECMWF analyses. Seven simulations are discussed: a control simulation, five sensitivity simulations in which the initial moisture availability is varied, and one simulation in which the coupling between moisture availability is suppressed. Changing the initial moisture availability adds a stochastic element to the development of deep convection. The results are interpreted in terms of the classical axisymmetric paradigm for tropical cyclone intensification with recent modifications.Spin‐up over land is favoured by the development of deep convection near the centre of the low circulation. As for tropical cyclones over sea, this convection leads to an overturning circulation that draws absolute angular momentum surfaces inwards in the lower troposphere leading to spin‐up of the tangential winds above the boundary layer. The intensification takes place within a moist monsoonal environment, which appears to be sufficient to support sporadic deep convection. A moisture budget for two mesoscale columns of air encompassing the storm shows that the horizontal import of moisture is roughly equal to the moisture lost by precipitation. Overall, surface moisture fluxes make a small quantitative contribution to the budget although, near the circulation centre, these fluxes appear to play an important role in generating local conditional instability. Suppressing the effect of rainfall on the moisture availability has little effect on the evolution of the low, presumably because, at any one time, deep convection is not sufficiently widespread.

Solar energy prediction and verification using operational model forecasts and ground-based solar measurements

The present study focuses on the predictions and verification of these predictions of solar energy using ground-based solar measurements from the Hellenic Network for Solar Energy and the National Observatory of Athens network, as well as solar radiation operational forecasts provided by the MM5 mesoscale model. The evaluation was carried out independently for the different networks, for two forecast horizons (1 and 2 days ahead), for the seasons of the year, for varying solar elevation, for the indicative energy potential of the area, and for four classes of cloud cover based on the calculated clearness index (kt): CS (clear sky), SC (scattered clouds), BC (broken clouds) and OC (overcast). The seasonal dependence presented relative rRMSE (Root Mean Square Error) values ranging from 15% (summer) to 60% (winter), while the solar elevation dependence revealed a high effectiveness and reliability near local noon (rRMSE ∼30%). An increment of the errors with cloudiness was also observed. For CS with mean GHI (global horizontal irradiance) ∼ 650 W/m2 the errors are 8%, for SC 20% and for BC and OC the errors were greater (>40%) but correspond to much lower radiation levels (<120 W/m2) of consequently lower energy potential impact. The total energy potential for each ground station ranges from 1.5 to 1.9 MWh/m2, while the mean monthly forecast error was found to be consistently below 10%.

InSAR Water Vapor Data Assimilation into Mesoscale Model MM5: Technique and Pilot Study

In this study, a technique developed to retrieve integrated water vapor from interferometric synthetic aperture radar (InSAR) data is described, and a three-dimensional variational assimilation experiment of the retrieved precipitable water vapor into the mesoscale weather prediction model MM5 is carried out. The InSAR measurements were available in the framework of the European Space Agency (ESA) project for the “Mitigation of electromagnetic transmission errors induced by atmospheric water vapor effects” (METAWAVE), whose goal was to analyze and possibly predict the phase delay induced by atmospheric water vapor on the spaceborne radar signal. The impact of the assimilation on the model forecast is investigated in terms of temperature, water vapor, wind, and precipitation forecast. Changes in the modeled dynamics and an impact on the precipitation forecast are found. A positive effect on the forecast of the precipitation is found for structures at the model grid scale or larger (1 km), whereas a negative effect is found on convective cells at the subgrid scale that develops within 1 h time intervals. The computation of statistical indices shows that the InSAR assimilation improves the forecast of weak to moderate precipitation ( ${ ).

Analysis of meteorological parameters for dense gas dispersion using mesoscale models

The current study focuses on characterizing the atmospheric details required for dense gas dispersion analysis resulting from release of cryogenic liquids like LNG. The study investigates the effectiveness of coupling the prognostic MM5 mesoscale model with the CALMET diagnostic model for producing meteorological conditions that is characteristic of dry and arid regions like Qatar, with non-neutral boundary conditions. MM5-CALMET wind fields and temperature data are compared with the meteorological field observations from the Doha International Airport (DIA) on a monthly basis, daily basis and hourly basis to study the effect of different averaging periods. The monthly averages replicate the annual patterns of meteorological parameters very well. However difference in observation and model are observed for wind speed and wind direction variable. The daily averages obtained from the model are in good agreement with the observation for wind speed and temperature. For hourly averaging, the model is found capable of mimicking the temperature of a given location, but not wind speed and direction. The prediction of wind direction parameter using MM5-CALMET is moderate for any averaging period. The sub-optimal performance of wind direction variable is attributed to grid resolution of vertical and horizontal layers of MM5-CALMET model. Additionally a case study is performed to illustrate the effect of variation of meteorological parameters on the lower flammability limits (LFL) resulting from flammable dense gas release of LNG. The case study demonstrates the issues that arise in a risk analysis study when “wrong” meteorological data could be used. The overall study indicates that utilizing the coarsest prognostic meteorological model output in a diagnostic model provides an effective option for generating meteorological inputs for dispersion studies.

Impact of 4DVAR assimilation of AIRS total column ozone observations on the simulation of Hurricane Earl

The Atmospheric Infrared Sounder (AIRS) provides twice-daily global observations of brightness temperature, which can be used to retrieve the total column ozone with high spatial and temporal resolution. In order to apply the AIRS ozone data to numerical prediction of tropical cyclones, a four-dimensional variational (4DVAR) assimilation scheme on selected model levels is adopted and implemented in the mesoscale non-hydrostatic model MM5. Based on the correlation between total column ozone and potential vorticity (PV), the observation operator of each level is established and five levels with highest correlation coefficients are selected for the 4DVAR assimilation of the AIRS total column ozone observations. The results from the numerical experiments using the proposed assimilation scheme for Hurricane Earl show that the ozone data assimilation affects the PV distributions with more mesoscale information at high levels first and then influences those at middle and low levels through the so-called asymmetric penetration of PV anomalies. With the AIRS ozone data being assimilated, the warm core of Hurricane Earl is intensified, resulting in the improvement of other fields near the hurricane center. The track prediction is improved mainly due to adjustment of the steering flows in the assimilation experiment.

Simulated effects of soil moisture on oasis self‐maintenance in a surrounding desert environment in Northwest China

ABSTRACTIrrigation is the only method to sustain oasis agriculture in northwest China. In this study, the effects of soil moisture perturbations on the oasis self‐maintenance mechanism were investigated using the mesoscale model MM5 with satellite observations of land‐surface parameters from MODIS data. Twelve simulations were performed, among which CTL (default simulation) and MOD (with parameters replaced with MODIS data) were used to evaluate the model results. Another 10 simulations with soil moisture perturbations (DRY and WET) assessed the influence of soil moisture on the oasis self‐maintenance mechanism. Independent of the initial soil moisture content, all simulations showed dramatic reductions of soil moisture in the initial several days of the simulation, due to the strong evapotranspiration in this arid environment. Both the DRY and WET perturbations led to substantial changes in surface heat flux partitioning and the oasis ‘cold‐wet’ effect, which were also verified by an analysis of the secondary circulation and moisture‐inversion level. Drying tends to have more influence than wetting, which indicates that irrigation should be performed more frequently than intensively to protect the oasis self‐maintenance mechanism.

Simulation of Severe Local Storm by Mesoscale Model MM5 and Validation Using Data from Different Platforms

During premonsoon season (March to May) convective developments in various forms are common phenomena over the Gangetic West Bengal, India. In the present work, simulation of wind squall on three different dates has been attempted with the help of mesoscale model MM5. The combination of various physical schemes in MM5 is taken as that found in a previous work done to simulate severe local storms over the Gangetic West Bengal. In the present study the model successfully simulates wind squall showing pressure rise, wind shift, wind surge, temperature drop, and heavy rainfall, in all cases. Convective cloud development and rainfall simulation by the model has been validated by the corresponding product from Doppler Weather Radar located at Kolkata and TRMM satellite product 3B42 (V6), respectively. It is found that the model is capable of capturing heavy rainfall pattern with up to three-hour time gap existing between simulation and observation of peak rainfall occurrence. In all simulations there is spatial as well as temporal shift from observation.

Mesoscale Structure of Torrential Rain Tropical Cyclone Over Liaodong Peninsula and the Effect of Complicated Topography

Using the NCAR nonhydrostatic mesoscale model MM5,the precipitation associated with typhoon Winnie( 9711) turning to Bohai Sea after landfall and topography forcing was simulated and its meso-scale structures was analyzed based on temperature of Block Body( TBB),disturbed streamline field and vertical velocity.The distributions of TBB display a clear mesoscale structure of convective cloud. The storm rainfall over Liaodong peninsula is closely related to mesoscale convec-tive system and topographic effect. The sensitivity experiments of topographic effect on the changes of precipitation and structure of typhoon Winnie show that:( 1) The local vertical circulations in north and east of Liaodong peninsula are favorable for formation and development of mesoscale convective cloud masses.( 2) Topography plays important roles in precipitation increment. The rainfall over the upwind slopes of the mountains and the precipitation cell intensity are increased with the topographic effect. Contrarily,the precipitation cell intensity is decreased without topographic effect. Heavy rainfall areas are corresponding to convergence zone.( 3) There exists significant increase of easterly wind velocity in the lower layer. Mesoscale cyclonic vortex systems are continuously generated and transported to the south of Liaodong peninsula which is favorable to sustain tropical cyclone( TC) intensity and induce heavy precipitation.( 4) The circulation of typhoon Winnie can be partly changed as the result of topography forcing. The local circulation of typhoon will be enhanced when cyclonic circulation initiated by topography forcing,and the rainfall will be increased accordingly,and vice versa.

A comparative evaluation of impact of domain size and parameterization scheme on simulation of tropical cyclones in the Bay of Bengal

AbstractA large number of processes and factors control the quality of simulations with a numerical weather prediction model and especially with mesoscale models; identification and optimization of these processes are critical for improving forecast skill. The importance of cumulus parameterization schemes in simulation of tropical cyclones was recognized early, and a large number of studies have addressed this issue. However, certain other aspects have received relatively less attention. In particular, unlike simulation with a global circulation model, a mesoscale simulation is characterized by a limited domain and hence inhomogeneous lateral boundary conditions that strongly affect the quality of the simulation. In this work, we investigate the relative impact of size of the model domain and the cumulus parameterization scheme on simulation of 10 cyclones over the Bay of Bengal during the period 1999–2009. For five domains with different spatial extents, simulations were carried out for three different cumulus parameterization schemes (Anthes‐Kuo, Grell, and Kain‐Fritsch2) for each of the 10 events (using the mesoscale model MM5). Our results show that the size of the domain also plays an equally critical role as the parameterization scheme in simulation of maximum intensity, track, and spatial structure of the cyclones. The impact of domain size is not linear; while each domain chosen is large enough, neither the largest nor the smallest domain provides the best simulation. However, there is consistency in the sense that a single domain emerges as best for intensity and track among the five considered. While the specific conclusions may depend on the ocean basin, the methodology is generic and can be applied to any ocean basin of cyclogenesis.

Mesoscale model to select the ideal location for new vineyard plantations in the Rioja qualified denomination of origin.

La Rioja is the region where the top rated wines from Spain come from and also the origin of one of the most prestigious wines in the world. It is worldwide recognized, not only for the quality of the vine, but also for the many factors involved in the process that are controllable by the farmer, such as fertilizers, irrigation, etc. Likewise, there are other key factors, which cannot be controlled that play, however, a crucial role in the quality of the wine, such as temperature, radiation, humidity, and rainfall. This research is focused on two of these factors: temperature and irradiation. The objective of this paper is to be able to recognize these factors, so as to ensure a proper decision criterion when selecting the best location for new vineyard plantations. To achieve this objective, a mesoscale model MM5 is used, and its performance is assessed and compared using different parameters, from the grid resolution to the physical parameterization of the model. Finally, the study evaluates the impact of the different parameterizations and options for the simulation of meteorological variables particularly relevant when choosing new vineyard sites (rainfall frequency, temperature, and sun exposure).

Land-Surface Heterogeneity Effects in the Planetary Boundary Layer

We investigate the cumulative added value of assimilating temperature, moisture, and wind observations in the three-dimensional non-hydrostatic Fifth-Generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model MM5 and use these forecasts to analyze the relationship between surface forcing and planetary boundary-layer (PBL) depth. A data assimilation methodology focused on the surface and the PBL, previously tested in a one-dimensional version of MM5, is applied to 29 May, 6 June, and 7 June 2002 during the International \(\hbox {H}_{2}\hbox {O}\) Project over the Southern Great Plains. Model-predicted PBL depth is evaluated against PBL depth diagnosed from data across 4,800 km of airborne lidar data (flight tracks 100–300 km long). The forecast with data assimilation verifies better against observations and is thus used to investigate the environmental conditions that govern PBL depth. The spatial structure in PBL depth is found to be most affected by spatial variations in surface buoyancy flux and capping inversion strength. The spatial scales of surface flux forcing reflected in the PBL depth are found through Fourier analysis and multiresolution decomposition. Correlations are \({<}0.50\) at scales of 64 km or less and increase at larger scales for 29 May and 6 June, but on 7 June low correlations are found at all scales, possibly due to greater within-PBL wind speeds, a stronger capping inversion on this day, and clouds. The results suggest a minimum scale, a function of wind speed, below which heterogeneity in surface buoyancy fluxes is not reflected directly in PBL depth.

Future variability of droughts in three Mediterranean catchments

In the present study, we analyze the magnitude and frequency of long-term droughts throughout the present century in Catalonia in the north-eastern Iberian Peninsula (Spain). In fact, this western Mediterranean region has recently suffered one of the most extreme dry episodes (2006–2008) in the last decades. This calls for further study of future perspectives of drought variability at the local scale. We selected three medium-sized catchments on the Catalan littoral: Fluvia, Tordera and Siurana. We employed both instrumental and simulated temperature and rainfall data to calculate two multi-scalar drought indices: the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Instrumental data consisted of several weather stations for a recent period: 1984–2008. Future projections covering the 2001–2100 period were extracted from a dynamical downscaling procedure at a 15-km horizontal grid resolution, nesting the mesoscale model MM5 into the atmosphere–ocean coupled model ECHAM5/MPI-OM, performed by the Meteorological Service of Catalonia. We calculated 24-month SPI and SPEI values for the instrumental and simulated periods, and no changes were found in drought variability for the early twenty-first century. For the mid-century, high climatic variability was detected, as extremely dry and wet periods might alternate according to the SPI values. At the end of the present century, we generally detected, particularly in the dry catchment of southern Catalonia, Siurana, more severe and longer droughts than the last extreme drought (2006–2008). There is a need to implement appropriate and specific adaptation strategies for water management of each catchment over the next decades to reduce the risk of the forecasted drought conditions.

Atmospheric simulations of southern South America's climate since the Last Glacial maximum

This study investigates the simulated present and past climate of southern South America through the use of the PSU/NCAR MM5 mesoscale model forced by Princeton GFDL global atmosphere-ocean model data. This approach is taken to obtain climate data with sufficiently high resolution to resolve the steep mountain ranges of the southern Andes, which generate large amounts of orographic precipitation. Results indicated that the region experienced northward shifted low level westerlies at and before 9000 years before present and shifts in upper level winds associated with the midlatitude jet culminated about 9000 years ago. A simple energy balance model indicates that the lower equilibrium line altitudes in the southern Andes during the Last Glacial maximum persisted into the early Holocene, resulting in an expansion of the area receiving net snow accumulation, particularly in eastern parts of the Andes mountains. Changes in simulated winds and precipitation in the lee of the southern Andes are consistent with Laguna Potrok Aike climate proxies.

Comparative assessment of soil moisture estimation from land surface model and satellite remote sensing based on catchment water balance

Land surface models and satellite remote sensing are among the modern soil moisture retrieval techniques that can be used over large areas. However, the lack of ‘ground truth’ soil moisture measurements is still an obstacle in the evaluation and validation of soil moisture retrievals. In this study, a new scheme is used to assess soil moisture retrieval from both the NOAH Land surface Model (LSM) coupled with the fifth generation Mesoscale Model MM5 and the Advanced Microwave Scanning Radiometer AMSR-E. The proposed scheme is based on the strong correlation between changes in soil storage from rainfall runoff events and changes in the retrieved soil moisture either from the MM5-NOAH LSM or the AMSR-E. The aim of this study is to compare the application of the proposed scheme between these two different approaches for soil moisture estimation. The MM5-NOAH LSM provides soil moisture estimations at three different layers with depths 0–10 cm (surface layer 1), 10–40 cm (layer 2) and 40–100 cm (layer 3). In this study, the combined soil moisture over the top two layers (first and second) and the combined soil moisture over the first three layers (first, second and third) are used to account for the entire soil column for assessing the estimated soil moisture using changes in the storage from the water balance. The results have shown that the MM5 soil moisture from the combined top two layers has the better performance than either of the individual layers when compared to the catchment water storage. The results also show that the MM5-NOAH LSM soil moisture estimates have a slightly better performance than the AMSR-E surface soil moisture measurement. This preliminary assessment shows the benefits of using hydrological data in the validation of soil moisture retrieval methods.

Error Correction Modelling of Wind Speed Through Hydro-Meteorological Parameters and Mesoscale Model: A Hybrid Approach

Accurate estimation of wind speed is essential for many hydrological applications. One way to generate wind velocity is from the fifth generation PENN/NCAR MM5 mesoscale model. However, there is a problem in using wind speed data in hydrological processes due to large errors obtained from the mesoscale model MM5. The theme of this article has been focused on hybridization of MM5 with four mathematical models (two regression models- the multiple linear regression (MLR) and the nonlinear regression (NLR), and two artificial intelligence models – the artificial neural network (ANN) and the support vector machines (SVMs)) in such a way so that the properly modelled schemes reduce the wind speed errors with the information from other MM5 derived hydro-meteorological parameters. The forward selection method was employed as an input variable selection procedure to examine the model generalization errors. The input variables of this statistical analysis include wind speed, temperature, relative humidity, pressure, solar radiation and rainfall from the MM5. The proposed conjunction structure was calibrated and validated at the Brue catchment, Southwest of England. The study results show that relatively simple models like MLR are useful tools for positively altering the wind speed time series obtaining from the MM5 model. The SVM based hybrid scheme could make a better robust modelling framework capable of capturing the non-linear nature than that of the ANN based scheme. Although the proposed hybrid schemes are applied on error correction modelling in this study, there are further scopes for application in a wide range of areas in conjunction with any higher end models.

Verification of the MM5 model using radiosonde data from Madrid–Barajas Airport

Vertical profiles of temperature, water vapor and wind field were traditionally obtained from radiosonde observations for the analysis of mesoscale phenomena. The scarce amount of radiosonde data available and the inadequate temporal and spatial resolution, motivated the development of prognostic soundings derived from Numerical Weather Prediction (NWP) models. Their use should be subject to previous quality verification of model outputs. This work is focused on the evaluation of the NCAR/Penn State Fifth Generation Mesoscale Model MM5 outputs under snow precipitation conditions in the Sierra de Guadarrama (Madrid). A comparison of forecasted vertical profiles of temperature, water vapor density and wind field with those observed by the Madrid–Barajas Airport rawinsonde was carried out. The results showed that the MM5 vertical profiles were able to represent thermodynamic conditions during winter precipitation events. Correlation coefficients of temperature and water vapor were close to 1 at both times. Wind field forecast was also accurate since wind direction and wind speed correlation coefficients were statistically significant for a 95% confidence. It was also found that MM5 simulations remained accurate after 24h from the initialization.

Impacts of inhomogeneous landscapes in oasis interior on the oasis self-maintenance mechanism by integrating numerical model with satellite data

Abstract. The impacts of inhomogeneity of the oasis interior on the oasis self-maintenance mechanism are investigated by using the mesoscale model MM5 (the fifth-generation Pennsylvania State University National Center for Atmospheric Research (NCAR) mesoscale model) with satellite observations of land use types, vegetation fraction and surface-layer soil moisture from MODIS (Moderate Resolution Imaging Spectroradiometer) data. Four simulations were performed, among which the CTL (control simulation) and MOD (moderated simulation with parameters replaced by MODIS data) were used to validate the model results; EXP1 (experiment 1) and EXP2 (experiment 2) were designed to study the inhomogeneity of oasis interior. Results show that the changes of oasis heterogeneity influence the surface heat-flux partitioning, which leads to a larger "cold-wet" effect over the oasis. Vertical sections of humidity illustrate the existence of a moisture-inversion level, and the deeper moisture inversion of EXP1 and EXP2 further indicates that the relative homogeneity in the oasis interior helps produce stronger humidity inversion over the oasis, thus limiting evaporation. This is further verified by the analysis of the secondary circulation, which shows that the more homogeneous land surface conditions lead to stronger secondary circulation and less turbulent drafts over the oasis interior, playing a positive role in the oasis self-maintenance and development.

Role of mesoscale factors at the onset of deep convection on hailstorm days and their relation to the synoptic patterns

Hailstorm forecast is a challenging task. The development of convective events is related to the synoptic environment as well as to the mesoscale factors, whose characteristics and evolution depend greatly on the topography of the study zone. This paper studies the mesoscale factors conditioning the beginning of deep convection in the 12 main events of severe hail in the Middle Ebro Valley, Spain, between 2001 and 2008. Previous results have enabled to classify the hailstorm days into five clusters, according to the atmospheric situation at a synoptic scale at low and mid‐tropospheric levels. Mesoscale factors that enhance the development of convection, such us convective instability, water vapor convergence and the low-level wind, have been studied using the Mesoscale Model MM5. The synoptic anomalies observed on the study days have been related to the mesoscale features responsible for the beginning of deep convection. The results show well-defined patterns with clear differences between the days belonging to the different clusters. The weight and the spatial patterns of the three selected factors are distinct in days of different clusters and lead to particular spatial precipitation patterns. This mesoscale analysis and its bidirectional relation to the synoptic anomalies and the spatial distribution of hail precipitation constitute a potentially useful tool for forecasting convective events in the study area.

Verification of precipitation forecasts of MM5 model over Epirus, NW Greece, for various convective parameterization schemes

Abstract. The mesoscale meteorological model MM5 is applied to 22 selected days with intense precipitation in the region of Epirus, NW Greece. At first, it was investigated whether and to what extend an increased horizontal resolution (from 8 to 2 km) improves the quantitative precipitation forecasts. The model skill was examined for the 12-h accumulated precipitation recorded at 14 meteorological stations located in Epirus and by using categorical and descriptive statistics. Then, the precipitation forecast skill for the 2 km grid was studied: (a) without and (b) with the activation of a convective parameterization scheme. From the above study, the necessity of the use of a scheme at the 2 km grid is assessed. Furthermore, three different convective parameterization schemes are compared: (a) Betts-Miller, (b) Grell and (c) Kain-Fritsch-2 in order to reveal the scheme, resulting in the best precipitation forecast skill in Epirus. Kain-Fritsch-2 and Grell give better results with the latter being the best for the high precipitation events.

The role of nocturnal Low-Level-Jet in nocturnal convection and rainfalls in the west Mediterranean coast: the episode of 14 December 2010 in northeast of Iberian Peninsula

Abstract. The night of 14 December 2010 radar images of the Spanish Weather Agency recorded a large rain band that moved offshore at the Northeast coast of the Iberian Peninsula. MM5 mesoscale model is used to study the atmospheric dynamics during that day. A Nocturnal Low Level Jet (NLLJ) generated by an inertial oscillation that brings cold air to the coast from inland has been simulated in the area. This cold air interacts with a warmer air mass some kilometers offshore. According to the MM5 mesoscale model simulation, the cold air enhances upward movements of the warm air producing condensation. Additionally, there is a return flow to the coastline at 600–900 m high. This warm air mass interacts again with the cold air moving downslope, also producing condensation inland. The simulation for the night before this episode shows large drainage winds with a NLLJ profile, but no condensation areas. The night after the 14th the simulation also shows drainage winds but without a NLLJ profile. However, an offshore convergence area was produced with a returned flow, but no condensation inland occurred. This fact is in agreement with radar observations which reported no precipitation for these two days. Consequently, NLLJ in combination with a synoptic wind over the sea could enhance condensation and eventually precipitation rates in the Mediterranean Iberian coast.