Weather Research Forecasting Model Research Articles

WRF model sensitivity to choice of PBL and microphysics parameterization for an advection fog event at Barkachha, rural site in the Indo-Gangetic basin, India

The present study evaluates the performance of four planetary boundary layer (PBL) parameterization schemes combined with five cloud microphysics schemes in Weather Research Forecasting (WRF) model, specifically for an advection fog event occurred during 4–6 December 2014 at Barkachha, rural site in the Indo-Gangetic plain (IGP). For this purpose, the model was configured over the IGP with 2-km horizontal resolution, and results are compared with detailed micrometeorological data (surface meteorological parameters and fluxes, radiative fluxes, and surface layer wind profiles) gathered during the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) Integrated Ground Observational Campaign (IGOC) site located in the IGP. The meteorological conditions conducive for the fog formation have been evaluated. All of the tested PBL-microphysics combination showed substantial bias for surface temperature, radiation fluxes, and wind speed. None of the combination found to be superior in predicting the fog event; however, the local MYNN2.5 combination with the WSM3, WSM6, and Lin microphysics obtained slightly better result at the study location. In general, judging from all simulations of liquid water content (as an indicator for the fog), the above combinations were able to simulate the current fog event but the fog onset, duration, and dissipation were particularly offset.

Drought Prediction for Areas with Sparse Monitoring Networks: A Case Study for Fiji

Hybrid drought prediction models were developed for areas with limited monitoring gauges using the APEC Climate Center Multi-Model Ensemble seasonal climate forecast and machine learning models of Extra-Trees and Adaboost. The models provide spatially distributed detailed drought prediction data of the 6-month Standardized Precipitation Index for the case study area, Fiji. In order to overcome the limitation of a sparse monitoring network, both in-situ data and bias-corrected dynamic downscaling of historical climate data from the Weather Research Forecasting (WRF) model were used as reference data. Performance measures of the mean absolute error as well as classification accuracy were used. The WRF outputs reflect the topography of the area. Hybrid models showed better performance than simply bias corrected forecasts in most cases. Especially, the model based on Extra-Trees trained using the WRF model outputs performed the best in most cases.

Projected changes in dust emissions and regional air quality due to the shrinking Salton Sea

Abstract The Salton Sea lake level in California is expected to transition in 2018 from a period of gradual decline to a new era of rapid decline that will expose about 40% of the year 2000 lakebed to wind erosion by 2030. The newly exposed Playa substrate can emit large amounts of particulate matter (PM) and thus degrade regional air quality. We use the Weather Research Forecast model (WRF-Chem) to estimate changes in dust aerosol emission and distribution in the Salton Sea region from 2000 to 2030. First, we evaluate simulations of present day wind speed, mineral dust emission, concentration, and optical depth over the region. WRF-Chem at 4 km spatial resolution satisfactorily reproduces the present-day spatio-temporal pattern of dust emission. With an estimated 38% exposure of the Salton Sea by 2030, the domain-averaged PM10 in the 2 × 2 degree domain enclosing the Sea increases on average by 11% and by nearly a factor of ten in localized source areas. The simulated increases in dust emission are consistent with earlier empirical estimates although our estimates are comparatively lower. Our regional model provides more spatially detailed and quantitative attribution of the projected air quality degradation. For example, our model suggests that newly exposed playa emissions will emanate more from the southwest than southeast side of the lake, even though most of the new playa will be on the southeast side. These results may inform decisions that affect trade-offs between environmental quality, human health, and water-use issues in the Salton Sea region.

A study comparison of two system model performance in estimated lifted index over Indonesia.

Lifted index (LI) is one of atmospheric stability indices that used for thunderstorm forecasting. Numerical weather Prediction Models are essential for accurate weather forecast these day. This study has completed the attempt to compare the two NWP models these are Weather Research Forecasting (WRF) model and Global Forecasting System (GFS) model in estimates LI at 20 locations over Indonesia and verified the result with observation. Taylor diagram was used to comparing the models skill with shown the value of standard deviation, coefficient correlation and Root mean square error (RMSE). This study using the dataset on 00.00 UTC and 12.00 UTC during mid-March to Mid-April 2017. From the sample of LI distributions, both models have a tendency to overestimated LI value in almost all region in Indonesia while the WRF models has the better ability to catch the LI pattern distribution with observation than GFS model has. The verification result shows how both WRF and GFS model have such a weak relationship with observation except Eltari meteorologi station that its coefficient correlation reach almost 0.6 with the low RMSE value. Mean while WRF model have a better performance than GFS model. This study suggest that estimated LI of WRF model can provide the good performance for Thunderstorm forecasting over Indonesia in the future. However unsufficient relation between output models and observation in the certain location need a further investigation.

GHI calculation sensitivity on microphysics, land- and cumulus parameterization in WRF over the Reunion Island

The sensitivity of different microphysics and dynamics schemes on calculated global horizontal irradiation (GHI) values in the Weather Research Forecasting (WRF) model is studied. 13 sensitivity simulations were performed for which the microphysics, cumulus parameterization schemes and land surface models were changed. Firstly we evaluated the model's performance by comparing calculated GHI values for the Base Case with observations for the Reunion Island for 2014. In general, the model calculates the largest bias during the austral summer. This indicates that the model is less accurate in timing the formation and dissipation of clouds during the summer, when higher water vapor quantities are present in the atmosphere than during the austral winter. Secondly, the model sensitivity on changing the microphysics, cumulus parameterization and land surface models on calculated GHI values is evaluated. The sensitivity simulations showed that changing the microphysics from the Thompson scheme (or Single-Moment 6-class scheme) to the Morrison double-moment scheme, the relative bias improves from ~45% to ~10%. The underlying reason for this improvement is that the Morrison double-moment scheme predicts the mass and number concentrations of five hydrometeors, which help to improve the calculation of the densities, size and lifetime of the cloud droplets. While the single moment schemes only predicts the mass for less hydrometeors. Changing the cumulus parameterization schemes and land surface models does not have a large impact on GHI calculations.

Implications of employing detailed urban canopy parameters for mesoscale climate modelling: a comparison between WUDAPT and GIS databases over Vienna, Austria

ABSTRACTOne of the major obstacles to using numerical weather prediction models for guidance on mitigating urbanization's impact on local and regional climate is the lack of detailed and model ready morphological data at urban scale. The World Urban Database and Access Portal Tool (WUDAPT) is a recent project developed to extract climate relevant information on urban areas, in the form of local climate zones (LCZs), out of remote sensing imagery. This description of the urban landscape has been tested and used for parameterization of different urban canopy models (UCM) for mesoscale studies. As detailed information is usually bounded within cities' centres, crowdsourced and remote sensing data offer the possibility to move beyond the old barriers of urban climate investigations by studying the full range of variation from the urban core to the periphery and its related impacts on local climate. Thus, for this study we sought to compare the relative impact of using the WUDAPT methodology versus a simplified definition of the urban morphology extracted out of detailed GIS information to initialize a regional weather model and compare the output against official and crowdsourced weather station networks. A case study over Vienna, Austria was conducted using the weather research forecasting (WRF) model, coupled with the building effect parameterization and building energy models (BEP–BEM) in five distinct seasonal periods. Results demonstrated that using detailed GIS data to derive morphological descriptions of LCZs for mesoscale studies provided only a marginal overall improvement over using the default WUDAPT parameters based on the ranges proposed by Stewart and Oke (2012). The findings also highlighted the importance of developing techniques that are better at capturing the morphological heterogeneity across the entire urban landscape and thus improve our understandings of UCM performance over urban areas.

Impact of model resolution on simulating the water vapor transport through the central Himalayas: implication for models\u2019 wet bias over the Tibetan Plateau

Current climate models commonly overestimate precipitation over the Tibetan Plateau (TP), which limits our understanding of past and future water balance in the region. Identifying sources of such models’ wet bias is therefore crucial. The Himalayas is considered a major pathway of water vapor transport (WVT) towards the TP. Their steep terrain, together with associated small-scale processes, cannot be resolved by coarse-resolution models, which may result in excessive WVT towards the TP. This paper, therefore, investigated the resolution dependency of simulated WVT through the central Himalayas and its further impact on precipitation bias over the TP. According to a summer monsoon season of simulations conducted using the weather research forecasting (WRF) model with resolutions of 30, 10, and 2 km, the study found that finer resolutions (especially 2 km) diminish the positive precipitation bias over the TP. The higher-resolution simulations produce more precipitation over the southern Himalayan slopes and weaker WVT towards the TP, explaining the reduced wet bias. The decreased WVT is reflected mostly in the weakened wind speed, which is due to the fact that the high resolution can improve resolving orographic drag over a complex terrain and other processes associated with heterogeneous surface forcing. A significant difference was particularly found when the model resolution is changed from 30 to 10 km, suggesting that a resolution of approximately 10 km represents a good compromise between a more spatially detailed simulation of WVT and computational cost for a domain covering the whole TP.

Feedback effect of electric field force on electrification and charge structure in thunderstorm

The electrification within the thunderstorm, caused mainly by inductive and noninductive charging mechanism, can produce strong local electric field inside the thundercloud. Due to the resulting electric field force, the vertical velocity of the graupel and hail particles which are the main in-cloud charge carriers, would change. As a feedback, this variation could affect the original electrification and charge structure of the thunderstorm. In order to investigate such a feedback effect, a weather research forecasting (WRF) model coupled with explicit lightning physics including charging and discharge lightning scheme (hereafter WRF-Elec) is employed and modified in this study. We derive the formulas for calculating the mass-weighted mean terminal velocities of graupel and hail under the balance among gravity, resistance and electric field force. Then, the National Sever Storm Laboratory (NSSL) two-moment bulk microphysics scheme is modified by adding the calculating code with consideration of electric field force (EFF) acting on the fall speed of graupel and hail particles. Eventually, the two-coupled WRF-Elec is developed successfully.#br#Based on this modified WRF-Elec, sensitivity tests are conducted to quantitatively investigate the influences of EFF on the thunderstorm electrification and the corresponding charge structure in an idealized supercell case. The results show that during the rapid enhancement of the thunderstorm, the grid-scale mass-weighted mean fall speed of graupel and hail vary significantly in consideration of EFF, with the maximum values both exceeding 4 m/s, although this situation occurs within a local area and lasts a short time. The action of EFF tends to enhance the falling of graupel and weaken the falling of hail. The influences of EFF on those graupel and hail particles with smaller-size and lower number concentration are stronger, as determined by composite factors of the strength and polarity of electric field, the diameter and number concentration of graupel and hail, and their charge density and polarity as well. The adjustment of the terminal velocity of the graupel and hail in consideration of EFF, eventually results in increasing the rate of both inductive and noninductive charge separation, where the inductive charging is the much more significant one. This leads to a grid-scale total charge density variation of -0.6-1.2 nC/m3 and a redistribution of the charge structure in the thunderstorm, and correspondingly, an increase of the local vertical electric field by 5 kV/m, thus producing stronger lightning eventually. In addition, due to the effect of electric field force, the mass mixing ratio of four precipitation particles including graupel, hail, ice crystal and snow is changed in the ranges of -0.09-0.24, -0.16-0.04, -0.04-0.05, and -0.01-0.006 g/kg, respectively. Therefore, the electric field force in thunderstorm affects not only the electrification and charge structure, but also the microphysical process. Generally, the overall influence of EFF on electrification tends to be positive, and the feedback effect of EFF on the charge structure should not be neglected.

Vertical Ozone Concentration Profiles in the Arabian Gulf Region during Summer and Winter: Sensitivity of WRF-Chem to Planetary Boundary Layer Schemes

Air quality in the Middle East is changing due to extensive land conversion, intense industrialization and rapid urbanization. In this study, we analyze data from an ozonesonde station operated in Doha, Qatar, by the Qatar Environment and Energy Research Institute (QEERI). Ozonesondes were launched weekly at 13:00 LT (10:00 UTC) during a summer month (August 2015) representative of extremely hot and humid atmospheric conditions and during a winter period (January–February 2016) representative of cool conditions in the area. Unlike similar studies in the region, this work focuses on the lower troposphere and combines high frequency vertical measurement data with the use of the Weather Research Forecasting model coupled with Chemistry (WRF-Chem). A sensitivity study was conducted to identify the most representative planetary boundary layer (PBL) parameterization. Although all three parameterizations that were examined produced similar results, the Yonsei University (YSU) PBL scheme was found to be statistically superior. Comparisons of model predictions against observations show high correlation coefficients and encouragingly low biases in all meteorological variables. During wintertime, ozone is well predicted overall (fractional bias = –0.1). Results from the summertime comparison are more challenging and point towards possible biases in the anthropogenic emission inventory of the Middle East, especially for rapidly-changing urban environments.

Effect of the Initial Vortex Size on Intensity Change in the WRF‐ROMS Coupled Model

AbstractNumerous studies have demonstrated that the tropical cyclone (TC) induced sea surface temperature (SST) cooling strongly depends on the preexisting oceanic condition and TC characteristics. However, very few focused on the correlation of SST cooling and the subsequent intensity with TC size. Therefore, a series of idealized numerical experiments are conducted using the Weather Research Forecasting (WRF) model coupled with the Regional Ocean Model System (ROMS) model to understand how the vortex size is related to SST cooling and subsequent intensity changes of a stationary TC‐like vortex. In the uncoupled experiments, the radius of maximum wind (RMW) and size (radius of gale‐force wind (R17)) both depend on the initial size within the 72 h simulation. The initially small vortex is smaller than the medium and large vortices throughout its life cycle and is the weakest. In other words, thermodynamic processes do not contribute as much to the R17 change as the dynamic processes proposed (e.g., angular momentum transport) in previous studies. In the coupled experiments, the area‐averaged SST cooling induced by medium and large TCs within the inner‐core region is comparable due to the similar surface winds and thus mixing in the ocean. Although a stronger SST cooling averaged within a larger region outside the inner‐core is induced by the larger TC, the intensity of the larger TC is more intense. This is because that the enthalpy flux in the inner‐core region is higher in the larger TC than that in the medium and small TCs.

Using numerical modelling in the simulation of mass fish death phenomenon along the Central Coast of Vietnam

A two-dimensional model was used to reconstruct scenarios related to the mass fish death phenomenon that occurred along the Central Coast of Vietnam. First, a Weather Research Forecasting model was used to simulate the wind field during April 2016, and was then used as an input to the two-dimensional (2D) model. Second, the calibration of the 2D model showed high conformity in both the phases and amplitude between the simulated and observed water levels. The simulation results of two scenarios, S1 and S2, were highly recommended for explaining the mass fish death phenomenon that occurred along the coast from Ha Tinh Province to Thua Thien-Hue Province. The calculated results of water quality data combined with the toxic concentration measured in fish will ultimately enable the simulation of the delimiting pollution zones and will facilitate response solutions when a similar phenomenon occurs in the future.

Numerical simulation of 23 June 2016 Yancheng City EF4 tornadic supercell and analysis of lightning activity

Based on the Weather Research Forecasting (WRF) model that features charging and discharging parameterization, relationships between tornado, hail and lightning were investigated for a tornado-producing (EF4 intensity) supercell thunderstorm over Yancheng City in Jiangsu Province, China, on 23 June 2016. Based on a sounding at 0800, there was a low lifting condensation level, substantial convective available potential energy (CAPE), and strong vertical wind shear near Yancheng City, which promote supercell development. At 1400, observations revealed that hail production and a dramatic increase of positive cloud-to-ground flash rates occurred simultaneously, maximizing five minutes later. The tornado occurred 30 min after the hail production. The time of minimum positive cloud-to-ground flash rates was 15 min later. The simulation indicated that the tornadic supercell moved eastward and that positive cloud-to-ground flash rates increased dramatically at 1400, the same as observed, but their maximum was 5 min later than observed. The simulated updraft volume peaked at 1425 and the simulated downdraft volume maximized 5 min later, when the mesocyclone formed. Simulated reflectivities showed no hook echo and horizontal winds for different height at mid-low levels had a different cyclonic shear at 1430, favorable to mesocyclone formation. Based on the simulated results, the region of positively charged graupel ascended resulting from the region of high liquid water content was lifted by the strong updraft, forming a mid-level strong positive charge region. A lower negative charge region formed by the inductive charging mechanism of collisions between graupel and droplets at the bottom of the cloud, conducive to positive cloud-to-ground flashes.

Regional modelling of polycyclic aromatic hydrocarbons: WRF-Chem-PAH model development and East Asia case studies

Abstract. Polycyclic aromatic hydrocarbons (PAHs) are hazardous pollutants, with increasing emissions in pace with economic development in East Asia, but their distribution and fate in the atmosphere are not yet well understood. We extended the regional atmospheric chemistry model WRF-Chem (Weather Research Forecast model with Chemistry module) to comprehensively study the atmospheric distribution and the fate of low-concentration, slowly degrading semivolatile compounds. The WRF-Chem-PAH model reflects the state-of-the-art understanding of current PAHs studies with several new or updated features. It was applied for PAHs covering a wide range of volatility and hydrophobicity, i.e. phenanthrene, chrysene and benzo[a]pyrene, in East Asia. Temporally highly resolved PAH concentrations and particulate mass fractions were evaluated against observations. The WRF-Chem-PAH model is able to reasonably well simulate the concentration levels and particulate mass fractions of PAHs near the sources and at a remote outflow region of East Asia, in high spatial and temporal resolutions. Sensitivity study shows that the heterogeneous reaction with ozone and the homogeneous reaction with the nitrate radical significantly influence the fate and distributions of PAHs. The methods to implement new species and to correct the transport problems can be applied to other newly implemented species in WRF-Chem.

Evaluating Wind Speed by WRF Model over Northern Thailand

The aim of this research is to estimate wind speed for northern Thailand by using a high resolution regional climate model called Weather Research Forecasting (WRF) version 3.7. The model was forced by the Community Climate System Model version 3 (CCSM3) which is a coupled climate model for simulating global climate system. The period of study was 5 years interval (2000-2004). The spatial wind speed distribution was analyzed seasonally by using the Grid Analysis and Display system (GrADS). The 5-year averaged wind speed simulations were compared to 13 station observation data sets provided by the Thai Meteorological Department (TMD). The statistical analysis presented Root mean square error (RMSE) and correlation.

Internal variability of a dynamically downscaled climate over North America

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.

A Study of the Oklahoma City Urban Heat Island Effect Using a WRF/Single-Layer Urban Canopy Model, a Joint Urban 2003 Field Campaign, and MODIS Satellite Observations

The urban heat island effect (UHI) for inner land regions was investigated using satellite data, ground observations, and simulations with an Single-Layer Urban Canopy Parameterization (SLUCP) coupled into the regional Weather Research Forecasting model (WRF, http://wrf-model.org/index.php). Specifically, using the satellite-observed surface skin temperatures (Tskin), the intensity of the UHI was first compared for two inland cities (Xi’an City, China, and Oklahoma City (OKC)), which have different city populations and building densities. The larger population density and larger building density in Xi’an lead to a stronger skin-level UHI by 2 °C. However, the ground observed 2 m surface air temperature (Tair) observations showed an urban cooling island effect (UCI) over the downtown region in OKC during the daytime of 19 July 2003, from a DOE field campaign (Joint Urban 2003). To understand this contrast between satellite-based Tskin and ground-based Tair, a sensitivity study using WRF/SLUCP was analyzed. The model reproduced a UCI in OKC. Furthermore, WRF/Noah/SLUCM simulations were also compared with the Joint Urban 2003 ground observations, including wind speeds, wind directions, and energy fluxes. Although the WRF/SLUCM model failed to simulate these variables accurately, it reproduced the diurnal variations of surface temperatures, wind speeds, wind directions, and energy fluxes reasonably well.

Implementation of a two-way coupled atmosphere-ocean wave modeling system for assessing air-sea interaction over the Mediterranean Sea

It is generally accepted that the fluid layer surrounding Earth should be considered as a single system at short and longer spatiotemporal scales. The current knowledge on the complex mechanisms of atmosphere-ocean interactions is still insufficient. This translates to the simulation of atmosphere and ocean as a single fully coupled system constructing multi-scale, multi-model integrated modeling systems. In this study, a new two-way coupled atmosphere-ocean wave modeling system is introduced with overarching aim to thoroughly unveil the impact of waves on the sea surface roughness and the atmospheric properties. The newly developed system consists of the Weather Research Forecasting (WRF) model with Chemistry (WRF-Chem) and Hydrology (WRF-Hydro) as the atmospheric component and the Wave model (WAM) as the ocean wave component. WRF and WAM models are coupled using the OASIS Model Coupling Toolkit (OASIS3-MCT) that enables models to communicate and exchange the information required to refine their simulation results. CHAOS (Chemical Hydrological Atmospheric Ocean wave System) has been tested in a high-impact cyclonic system over the Mediterranean Sea employing one-way and two-way coupling simulations to assess the air-sea interactions, currently neglecting the chemical and hydrological capabilities. The encapsulation of the ocean waves in the atmospheric surface layer processes modifies the characteristics of atmospheric flow and determines the ocean wave generation. A remarkable finding is that the coupling of the two systems affects the air-sea momentum, enthalpy and moisture transfer determining the evolution of the cyclonic system. The interactions along the air-sea interface are also reflected in the vertical structure of troposphere and its properties. CHAOS in two-way coupling mode shows an overall improvement of the forecast skill up to 20% over the sea while positively affects the atmospheric predictability over the land.

Numerical simulation of tropical cyclone thane: role of boundary layer and surface drag parameterization schemes

In the recent times, several advanced numerical models are utilized for the prediction of the intensity, track and landfall time of a cyclone. Still there are number of issues concerning their prediction and the limitation of numerical models in addressing those issues. The most pertinent question is how intensive a cyclone can become before it makes a landfall and where the cyclone moves under the ambient large-scale flow. In this paper, detailed study has been carried out using Weather Research Forecast model with two boundary schemes to address the above question by considering a recent tropical cyclone in Bay of Bengal region of North Indian Ocean. In addition, the impact of the surface drag effect on the low-level winds and the intensity of the cyclone are also studied. The result reveals that large differences are noted in the ocean surface fluxes between YSU and MYJ with MYJ producing relatively higher fluxes than YSU. It is found that the YSU scheme produced a better simulation for the THANE cyclone in terms of winds, pressure distribution and cloud fractions. Comparison with available observations indicated the characteristics of horizontal divergence, vorticity and vector track positions produced by YSU experiment are more realistic than with MYJ and other experiments. However, when the drag coefficient is changed as 0.5 or 2.0 from the default values, appreciable changes in the surface fluxes are not noticed. A maximum precipitation is reported in YSU as compared to the MYJ PBL scheme for the tropical cyclone THANE.

Comparison between 3D-Var and 4D-Var data assimilation methods for the simulation of a heavy rainfall case in central Italy

Abstract. This work aims to provide a comparison between three dimensional and four dimensional variational data assimilation methods (3D-Var and 4D-Var) for a heavy rainfall case in central Italy. To evaluate the impact of the assimilation of reflectivity and radial velocity acquired from Monte Midia Doppler radar into the Weather Research Forecasting (WRF) model, the quantitative precipitation forecast (QPF) is used.The two methods are compared for a heavy rainfall event that occurred in central Italy on 14 September 2012 during the first Special Observation Period (SOP1) of the HyMeX (HYdrological cycle in Mediterranean EXperiment) campaign. This event, characterized by a deep low pressure system over the Tyrrhenian Sea, produced flash floods over the Marche and Abruzzo regions, where rainfall maxima reached more than 150 mm 24 h−1.To identify the best QPF, nine experiments are performed using 3D-Var and 4D-Var data assimilation techniques. All simulations are compared in terms of rainfall forecast and precipitation measured by the gauges through three statistical indicators: probability of detection (POD), critical success index (CSI) and false alarm ratio (FAR). The assimilation of conventional observations with 4D-Var method improves the QPF compared to 3D-Var. In addition, the use of radar measurements in 4D-Var simulations enhances the performances of statistical scores for higher rainfall thresholds.

Southwest Monsoon Change in Thailand Using the Regional Climate Model-WRF

Monsoon onset is one of important characteristics of southwest monsoon which directly influence to Thailand’s water management and agricultural planning. Most of total rainfall amounts in Thailand are provided by the monsoon. Weather Research Forecasting model (WRF) was used as a tool to simulate dialy total rainfall, upper and lower horizontal winds over current period (1990-1999) and future period (2030-2039). These variables are analyzed to study southwest monsoon onset change over Thailand. The simulations show that average monsoon onsets during 1990s and 2030s are in 13th and 20th May, respectively. Standard deviations for the onset were 3 days and 4 days for current and future period, respectively.