Weather Research And Forecasting Model Simulations Research Articles

Improving the modeled variability estimates of offshore winds in Northern Europe by nudging ASCAT-derived winds

Abstract The paper aims to demonstrate how to enhance the accuracy of offshore wind resource estimation, specifically by incorporating near-surface satellite-derived wind observations into mesoscale models. We utilized the Weather Research and Forecasting (WRF) model and applied observational nudging by integrating ASCAT data over offshore areas to achieve this. We then evaluated the accuracy of the nudged WRF model simulations by comparing them with data from ocean oil platforms, tall masts, and a wind Lidar mounted on a commercial ferry crossing the southern Baltic Sea. Our findings indicate that including satellite-derived ASCAT wind speeds through nudging enhances the correlation and reduces the error of the mesoscale simulations across all validation platforms. Moreover, it consistently outperforms the control and previously published WRF-based wind atlases. Using satellite-derived winds directly in the model simulations also solves the issue of lifting near-surface winds to wind turbine heights, which has been challenging in estimating wind resources at such heights. The comparison of the one-year-long simulations with and without nudging reveals intriguing differences in the sign and magnitude between the Baltic and North Seas, which vary seasonally. The pattern highlights a distinct regional pattern attributed to regional dynamics, sea surface temperature, atmospheric stability, and the number of available ASCAT samples.

Impact of Urban Representation on Simulation of Hurricane Rainfall

AbstractTaking the examples of Hurricane Florence (2018) over the Carolinas and Hurricane Harvey (2017) over the Texas Gulf Coast, the study attempts to understand the performance of slab, single‐layer Urban Canopy Model (UCM), and Building Environment Parameterization (BEP) in simulating hurricane rainfall using the Weather Research and Forecasting (WRF) model. The WRF model simulations showed that for an intense, large‐scale event such as a hurricane, the model quantitative precipitation forecast over the urban domain was sensitive to the model urban physics. The spatial and temporal verification using the modified Kling‐Gupta efficiency and Method for Object based Diagnostic and Evaluation in Time Domain suggests that UCM performance is superior to the BEP scheme. Additionally, using the BEP urban physics scheme over UCM for landfalling hurricane rainfall simulations has helped simulate heavy rainfall hotspots.

Signatures of Oceanic Wind Events in Convection-Resolving WRF Model Simulations

Abstract Analyses of cloud-top temperature and lightning characteristics of 48 Weather Research and Forecasting (WRF) Model–simulated ocean-based wind events, with 1-min temporal and 0.5-km horizontal resolution, revealed signatures similar to the corresponding 13 observed events detected by buoys and Coastal-Marine Automated Network (C-MAN) stations as shown in prior research on ocean-based wind events by the first author. These events occurred in the eastern Gulf of Mexico and in the Atlantic Ocean from Florida northward through South Carolina. The coldest WRF cloud-top temperature (WCTT) and peak WRF-estimated lightning flash rate values of the model-simulated events, where each event was required to have a negative vertical velocity of at least 10 m s−1 in the lowest 2 km associated with a convective storm, occurred at an average of 4.2 and 1.1 min prior to the events, respectively. With 36 of the events, the peak estimated flash rate occurred within 5 min of the coldest WCTT. Cloud depth typically increased as the WCTT decreased, and the maximum depth occurred at an average of 2.9 min prior to the events. Thermal cooling and precipitation loading provided negative buoyancy needed to help drive the wind events. Environmental characteristics of the model-simulated ocean-based wind events also resembled those associated with land-based wet downbursts, including moist air near the surface, lapse rates near moist adiabatic, and low cloud bases.

Height correction method based on the Monin–Obukhov similarity theory for better prediction of near-surface wind fields

We developed the height correction algorithm based on the Monin–Obukhov similarity theory for application in Weather Research and Forecasting (WRF) model outputs to correct the 10-m height definition and match weather station observations. Thirty simulations were conducted for April 2012 to validate the height correction algorithm against observations such as the automated surface observing system and automatic weather stations. The WRF model simulations were constructed with two nested domains with horizontal grid spacings of 10 and 1 km. The root mean square error of the diagnosed 10-m wind speed after applying the height correction algorithm was consistently reduced compared to the one before applying the algorithm over the innermost domain during the analysis period. The impact of the height correction on diagnosed wind speed was greater when the environment was unstable and the magnitude of the roughness length was large. Evaluation showed that a strong synoptic forcing condition results in a significant reduction in the bias of wind speed.

Evaluation of High-Resolution Land Cover Geographical Data for the WRF Model Simulations

Increased computing power has made it possible to run simulations of the Weather Research and Forecasting (WRF) numerical model in high spatial resolution. However, running high-resolution simulations requires a higher-detail mapping of landforms, land use, and land cover. Often, higher-resolution data have limited coverage or availability. This paper presents the feasibility of using CORINE Land Cover (CLC) land use and land cover data and alternative high-resolution global coverage land use/land cover (LULC) data from Copernicus Global Land Service Land Cover Map (CGLS-LC100) V2.0 in high-resolution WRF simulations (100 × 100 m). Global LULC data with a resolution of 100 m are particularly relevant for areas not covered by CLC. This paper presents the method developed by the authors for reclassifying land cover data from CGLS-LC100 to MODIS land use classes with defined parameters in the WRF model and describes the procedure for their implementation into the model. The obtained simulation results of the basic meteorological parameters from the WRF simulation using CLC, CGLS-LC100 and default geographical data from MODIS were compared to observations from 13 meteorological stations in the Warsaw area. The research has indicated noticeable changes in the forecasts of temperature, relative humidity wind speed, and direction after using higher-resolution LULC data. The verification results show a significant difference in weather predictions in terms of CLC and CGLS-LC100 LULC data implementation. Due to the fact that better results were obtained for CLC simulations than for CGLS-LC100, it is suggested that CLC data are first used for simulations in numerical weather prediction models and to use CGLS-LC100 data when the area is outside of CLC coverage.

Performance of the WRF Model for the Forecasting of the V-Shaped Storm Recorded on 11–12 November 2019 in the Eastern Sicily

During the autumn season, Sicily is often affected by severe weather events, such as self-healing storms called V-shaped storms. These phenomena cause significant total rainfall quantities in short time intervals in localized spatial areas. In this framework, this study analyzes the meteorological event recorded on 11–12 November 2019 in Sicily (southern Italy), using the Weather Research and Forecasting (WRF) model with a horizontal spatial grid resolution of 3 km. It is important to note that, in this event, the most significant rainfall accumulations were recorded in eastern Sicily. In particular, the weather station of Linguaglossa North Etna (Catania) recorded a total rainfall of 293.6 mm. The precipitation forecasting provided by the WRF model simulation has been compared with the data recorded by the meteorological stations located in Sicily. In addition, a further simulation was carried out using the Four-Dimensional Data Assimilation (FDDA) technique to improve the model capability in the event reproduction. In this regard, in order to evaluate which approach provides the best performance (with or without FDDA), the Root Mean Square Error (RMSE) and dichotomous indexes (Accuracy, Threat Score, BIAS, Probability of Detection, and False Alarm Rate) were calculated.

The generation mechanism of cold eddies and the related heat flux exchanges in the upper ocean during two sequential tropical cyclones

The impacts of two sequential tropical cyclones (TCs), Kyarr and Maha, [from October 24 to November 06, 2019, over the Arabian Sea (AS)] on upper ocean environments were investigated using multiple satellite observations, Argo float profiles and numerical model outputs. To obtain a realistic TC strength, the Weather Research and Forecasting (WRF) model was used to reproduce Kyarr and Maha. During Kyarr and Maha, three distinct cold patches were observed at the sea surface with a maximum sea surface cooling of approximately 5°C. The comparison between WRF model simulation results and ERA5 wind field showed that the WRF model simulation indicated high simulation accuracy with respect to the SST decrease in the AS under the influence of Kyarr and Maha’s wind stress curls. Meanwhile, concentration of chlorophyll a (chl-a) and positive relative vorticity of sea surface also appeared in the three cold patch areas. Through the use of eddy detection algorithms, three mesoscale cold cyclonic eddies were identified along the track of TC Kyarr, and the locations of these cold eddies were highly correlated with three obvious negative sea surface height anomalies (SSHAs). The radii of the three cold eddies were 69 km, 50 km, and 41 km. With a focus on the thermodynamic responses of the three cold eddy fields to Kyarr and Maha, the central regions of the three cold eddies were explored. The central regions of the three cold eddies exhibited relatively shallow mixed-layer depths (MLDs) and low mixed-layer temperatures (MLTs). The depth integrated heat (DIH) content was also calculated to explore the heat flux exchanges occurring in different layers in the upper 200 m of the centre of each eddy. The results showed that DIH in each eddy centre varied by one order of magnitude, accounting for between 127.3 MJ m-2 and 1220.0 MJ m-2 of heat loss. This study suggests that the effect of long forcing time on intense positive wind stress curls can produce upwelling caused by Ekman response, which is the main influencing factor of the three cold eddies generation mechanism. At the same time, the positive relative vorticity injected into the sea surface also has some contribution. TC-induced vertical mixing and upwelling (strengthened by unstable structures inside the cold eddies) cause substantial redistribution of the DIH, and related heat flux exchanges at different layers occur in the eddy fields.

Evaluating the mesoscale spatio-temporal variability in simulated wind speed time series over northern Europe

Abstract. As wind energy increases its share of total electricity generation and its integration into the power system becomes more challenging, accurately representing the spatio-temporal variability in wind data becomes crucial. Wind fluctuations impact power and energy systems, e.g. energy system planning, vulnerability to storm shutdowns, and available voltage stability support. To analyse such fluctuations and their spatio-temporal dependencies, time series of wind speeds at an hourly or higher frequency are needed. We provide a comprehensive evaluation of the global and mesoscale-model-derived wind time series against observations by using a set of metrics that we present as requirements for wind energy integration studies. We also perform a sensitivity analysis to find the best model setup of the Weather Research and Forecasting (WRF) model, focusing on evaluating the wind speed fluctuation metrics. The results show that using higher spatial resolution in the WRF model simulations improves the representation of temporal fluctuations; however, higher-spatial-resolution simulations often lower the correlations of wind time series with measurements. Thus, we recommend finer-spatial-resolution simulations for modelling power ramp or voltage stability studies but ERA5 rather than mesoscale simulations for studies where correlations with measurements are essential. We also show that the nesting strategy is an important consideration, and a smoother transition from the forcing data to the nested domains improves the correlations with measurements. All mesoscale model simulations overestimate the value of the spatial correlations in wind speed as estimated from observations. Still, the spatial correlations and the wind speed distributions are insensitive to the mesoscale model configuration tested in this study. Regarding these two metrics, mesoscale model simulations present more favourable results than ERA5.

Land–Atmosphere Interactions during GRAINEX: Planetary Boundary Layer Evolution in the Presence of Irrigation

Abstract This paper analyzed observations from the Great Plains Irrigation Experiment (GRAINEX) to better understand land–atmosphere (L–A) interactions and PBL evolution. This study is focused on a day when the largest forcing on the boundary layer originated from the land surface/land use. To examine these impacts, we also applied the Weather Research and Forecasting (WRF) Model. Results from the observations show that compared to nonirrigated areas, air temperature, wind speed, and PBL height (PBLH) were lower while dewpoint temperature and latent heat flux were higher over irrigated areas. Findings suggest that entrainment layer drying and differences in energy partitioning over irrigated and nonirrigated areas played an important role in PBL evolution. In the final hours of the day, the PBL collapsed faster over nonirrigated areas compared to irrigated. The WRF Model simulations agree with these observations. They also show that the extent of irrigation [expressed as irrigation fraction (IF)] in an area impacts L–A response. Under ∼60% IF, the latent heat flux and mixing ratio reach their highest value while temperature and PBLH are at their lowest, and sensible heat flux is near its lowest value. Results are reversed for ∼2% IF. It is concluded that irrigation notably impacts L–A interactions and PBL evolution.

Profiling the Planetary Boundary Layer Wind with a StreamLine XR Doppler LiDAR: Comparison to In-Situ Observations and WRF Model Simulations

Halo-Photonics StreamLine XR Doppler LiDAR measurements are performed using several scan configurations (Velocity Azimuth Display-VAD and Doppler Beam Swing-DBS) and elevation angles of 60° and 80°. The measurements are compared to wind observations conducted by various in situ instruments (tethered balloon, meteorological mast, and radiosondes). Good agreement is obtained, with R2 over 0.90 for wind speed and a standard error ≤ 18.6° for wind direction. The best performance was attained for lower elevation scans (60°), which is consistent with the higher spatial horizontal homogeneity exhibited by lower angle scans. VAD and DBS scans performed almost equally well with slight advantage for VAD in higher altitudes and for DBS for lower altitudes. The boundary layer structure along a diurnal cycle is analyzed by utilizing retrieved backscatter data and wind measurements in conjunction with Weather Research and Forecast (WRF) simulations. The presence of multiple inversions which allow the coexistence of different layers within the studied profile is also verified using data acquired by several radiosondes. Synergic use of LiDAR data with WRF simulations for low SNR regions is demonstrated.

Sensitivity analysis of an aerosol-aware microphysics scheme in Weather Research and Forecasting (WRF) during case studies of fog in Namibia

Abstract. Aerosol-aware microphysics parameterisation schemes are increasingly being introduced into numerical weather prediction models, allowing for regional and case-specific parameterisation of cloud condensation nuclei (CCN) and cloud droplet interactions. In this paper, the Thompson aerosol-aware microphysics scheme, within the Weather Research and Forecasting (WRF) model, is used for two fog cases during September 2017 over Namibia. Measurements of CCN and fog microphysics were undertaken during the AErosols, RadiatiOn and CLOuds in southern Africa (AEROCLO-sA) field campaign at Henties Bay on the coast of Namibia during September 2017. A key concept of the microphysics scheme is the conversion of water-friendly aerosols to cloud droplets (hereafter referred to as CCN activation), which could be estimated from the observations. A fog monitor 100 (FM-100) provided cloud droplet size distribution, number concentration (Nt), liquid water content (LWC), and mean volumetric diameter (MVD). These measurements are used to evaluate and parameterise WRF model simulations of Nt, LWC, and MVD. A sensitivity analysis was conducted through variations to the initial CCN concentration, CCN radius, and the minimum updraft speed, which are important factors that influence droplet activation in the microphysics scheme of the model. The first model scenario made use of the default settings with a constant initial CCN number concentration of 300 cm−3 and underestimated the cloud droplet number concentration, while the LWC was in good agreement with the observations. This resulted in droplet size being larger than the observations. Another scenario used modelled data as CCN initial conditions, which were an order of magnitude higher than other scenarios. However, these provided the most realistic values of Nt, LWC, MVD, and droplet size distribution. From this, it was concluded that CCN activation of around 10 % in the simulations is too low, while the observed appears to be higher reaching between 20 % and 80 %, with a mean (median) of 0.55 (0.56) during fog events. To achieve this level of activation in the model, the minimum updraft speed for CCN activation was increased from 0.01 to 0.1 m s−1. This scenario provided Nt, LWC, MVD, and droplet size distribution in the range of the observations, with the added benefit of a realistic initial CCN concentration. These results demonstrate the benefits of a dynamic aerosol-aware scheme when parameterised with observations.

Tornadoes in the Tyrrhenian regions of the Italian peninsula: The case study of 28 July 2019

On 28 July 2019 an EF2 tornado affected a small rural area in central Italy causing several damages and one casualty. The tornado was spawned by a thunderstorm embedded in a linear convective system that crossed the central Tyrrhenian regions of Italy. The environment was characterized by high values of convective available potential energy (CAPE) and deep layer wind shear (DLS). The severity of this type of events highlights the importance of carrying out multi-scale integrated analysis on tornado phenomena in the area, one of the most affected by these events in the Mediterranean and on which dedicated studies have not yet been carried out so far.Tornadoes in the area are identified in the years 1990–2021, allowing to perform a synoptic/mesoscale analysis of the main patterns associated to these events. The 32-year analysis is carried out using both radiosonde observations and ERA5 reanalysis.The average synoptic configuration is dominated by an upper level trough over the central Mediterranean Sea and by a low surface pressure area over northwestern Italy, with southwesterly upper-level winds over the Tyrrhenian Sea and higher-than-average northwesterly winds entering the western Mediterranean through the gulf of Lion. Moderate mean values of CAPE (about 700 J Kg−1) and DLS (about 15 m s−1) are found, and the linear shape of the hodograph indicates favorable conditions for multicell systems.High-resolution WRF (Weather Research and Forecasting) model simulations of the 28 July 2019 case study correctly reproduced the event and the structure of the storm. Extreme values of the typical instability parameters/indices denote an environment particularly favorable for tornado formation; some sensitivity tests permitted to evaluate the role of several forcing (Sea Surface Temperature, surface fluxes and orography) in the development and the trajectory of the storm.

Boundary Layer Characteristics Over Complex Terrain in Central Taiwan: Observations and Numerical Modeling

AbstractThe development of the atmospheric boundary layer and flow circulation becomes complicated over complex terrain. A field campaign involving the acquisition of tethersonde, ozonesonde and 10‐m meteorological tower observations was conducted during September 2–8, 2013, over the Puli Basin located in the mountainous area of central Taiwan to investigate the evolution of the planetary boundary layer (PBL) and flow circulation. In addition, numerical simulations using the Weather Research and Forecasting (WRF) model were performed to examine the three‐dimensional air flow variations. Analysis of the tethersonde data indicated a well‐mixed boundary layer structure and a steady westerly flow over the Puli Basin during the daytime that became further enhanced in the afternoon. The 600‐m resolution WRF model simulation showed that the enhanced wind flow in the afternoon was due to the inland penetration of the onshore sea breeze, which also transported high concentrations of O3 from the western metropolitan area into the basin. During the nighttime, a stable boundary layer formed, above which a nocturnal low‐level jet formed throughout the campaign period in the Puli Basin. The WRF model is able to reproduce the general variations in the wind flows and thermal structures. Furthermore, the diagnostic PBL height estimated based on the critical Richardson number provides an enhanced understanding of the evolutionary characteristics of the PBL over complex terrain.

Cloud-Resolving-Model Simulations of Nocturnal Precipitation over the Himalayan Slopes and Foothills

Abstract A numerical experiment with a 2-km resolution was conducted using the Weather Research and Forecasting (WRF) Model to investigate physical processes driving nocturnal precipitation over the Himalayas during the mature monsoon seasons between 2003 and 2010. The WRF Model simulations of increases in precipitation twice a day, one in the afternoon and another around midnight, over the Himalayan slopes, and of the single nocturnal peak over the Himalayan foothills were reasonably accurate. To understand the synoptic-scale moisture transport and its local-scale convergence generating the nocturnal precipitation, composite analyses were conducted using the reanalysis dataset and model outputs. In the synoptic scale, moisture transport associated with the westward propagation of low pressure systems was found when nocturnal precipitation dominated over the Himalayan slopes. In contrast, moisture was directly provided from the synoptic-scale monsoon westerlies for nocturnal precipitation over the foothills. The model outputs suggested that precipitation occurred on the mountain ridges in the Himalayas during the afternoon and expanded horizontally toward lower-elevation areas through the night. During the nighttime, the downslope wind was caused by radiative cooling at the surface and was intensified by evaporative cooling by hydrometeors in the near-surface layer. As a result, convergence between the downslope wind and the synoptic-scale flow promoted nocturnal precipitation over the Himalayas and to the south, as well as the moisture convergence by orography and/or synoptic-scale circulation patterns. The nocturnal precipitation over the Himalayas was not simulated well when we used the coarse topographic resolution and the smaller number of vertical layers.

Evaluation of snow depth and snow cover represented by multiple datasets over the Tianshan Mountains: Remote sensing, reanalysis, and simulation

AbstractMountain snowpacks play important roles in water resource and ecological system. However, existing snow depth products show great uncertainties across the Tianshan Mountains, Central Asia. This study evaluated and compared four snow depth datasets over the Tianshan Mountains, including snow depth datasets from ERA5, ERA5‐Land, passive microwave, as well as a dynamically downscaled simulation by Weather Research and Forecasting (WRF) model. The snow depth was evaluated against in situ observations while the snow cover extent was evaluated by interactive multisensor snow and ice mapping system (IMS) snow cover. Furthermore, the snow‐related metrics, such as annual mean snow depth and snow cover days, were compared among the four datasets. The results showed that the spatial patterns of snow‐related metrics were relatively consistent among datasets, although discrepancies existed in magnitude. Additionally, the temporal variations in snow‐related metrics depended on the dataset employed. The simulated snow depth from WRF got the lowest bias in daily snow depth value against the in situ observations (mean bias = 0.12 cm, root mean square error = 2.08 cm), additionally, it had the best performance in classifying correct snow grids compared with IMS (probability of detection = 0.766). It also outperformed in annual mean snow depth and snow cover days by 47.2 and 13.3% compared with ERA5‐Land snow depth. This study highlights the confidence in characterizing both the spatial pattern and temporal variations of snow depth products based on WRF model simulation.

Sensitivity of WRF-derived hydrometeorological extremes to sea surface temperatures in regions with complex topography and diverse climate

This study investigates the impact of sea surface temperature (SST) describing the lower boundary of Weather Research and Forecasting (WRF) model on the extreme weather events that occurred on the Mediterranean (MED) and the Eastern Black Sea (EBS) regions of Turkey. For each region, one extreme event case is selected and characterized as a summer convective system in EBS and as a winter synoptic system in MED region. The SST impact on the WRF model forecasts of these events is accomplished in two ways. First, the SST analysis is conducted by making a 10-days simulation for each event with and without activating the SST options (update and skin options) available in the model configuration. In these runs, the selected initial and boundary condition datasets, Global Forecasting System (GFS) for the MED region and the ERA5 for the EBS regions, provide corresponding internal SST data. Second, the prediction performance of the model is evaluated among the simulations of non-external, time-varying (GFS and ERA5 SST) and external, time–varying, high-resolution SST products (The Group for High Resolution Sea Surface Temperature; GHRSST, Medspiration, and NCEP) for each event. The results show that the WRF model simulations, even for short-term event predictions, are highly sensitive to time-variant SST options. The overestimation and high spreading feature of maximum and total precipitation are realistically reduced by time-variant SST products. The Medspiration and the NCEP sources for the MED region and the GHRSST and the Medspiration sources for the EBS region yielded warmer SSTs among the simulations. By establishing the amplified air-sea interactions, these sources provide more appropriate peak precipitation distributions in both regions. Furthermore, based on this study, the effect of using high-resolution SST (GHRSST and Medspiration) is more prominent in predicting convective event developed over complex topography of the EBS while the resolution effect is not much critical for synoptic system simulation even under the complex topography in MED. Lastly, the highest mean correlation of conditional hourly rain is calculated as 0.65 with the Medspiration product on MED and 0.48 with the GHRSST product on the EBS region.

Sensitivity of South Asian summer monsoon simulation to land surface schemes in Weather Research and Forecasting model

AbstractThe land surface scheme is crucial for the performance of regional climate models in dynamic downscaling application. In this study, we explore the sensitivity of the simulation with 10‐km resolution Weather Research and Forecasting (WRF) model to the land surface schemes in simulating South Asian summer monsoon. The WRF simulations for 19 summers from 2000 to 2018 are conducted with four different land surface schemes including Exp‐CLM4, Exp‐Noah‐MP, Exp‐PX, and Exp‐SSiB, with that the initial and boundary conditions for the WRF model simulations are provided from the NCEP‐FNL data. The ERAI reanalysis data, GHCN‐CAMS, and CRU gridded data are used to comprehensively evaluate the WRF simulations. Compared with verification data, the WRF model can reasonably capture the spatial patterns of summer mean large‐scale atmospheric circulation, 2‐m temperature and precipitation. The simulation results, however, are sensitive to the option of land surface scheme. The performance of Exp‐CLM4 and Exp‐SSiB is better than that of Exp‐Noah‐MP and Exp‐PX assessed by multivariable integrated evaluation (MVIE) method. To explore the dynamic and physical mechanisms behind the WRF model sensitivity to land surface schemes, the differences in the surface energy balance between the ensemble means Ens‐CLM4‐SSiB and Ens‐NoanMP‐PX are analysed in detail. The results illustrate that the intensity of the simulated sensible heat flux over South Asia is weaker in Ens‐CLM4‐SSiB than that in Ens‐NoahMP‐PX. The simulated wind fields are influenced due to the geostrophic adjustment process caused by large differences in geopotential height; thus, the simulations of 2‐m temperature and precipitation are all affected.

Simulation of summer climate over Central Asia shows high sensitivity to different land surface schemes in WRF

Land surface processes are vital to the performance of regional climate models in dynamic downscaling application. In this study, we investigate the sensitivity of the simulation by using the weather research and forecasting (WRF) model at 10-km resolution to the land surface schemes over Central Asia. The WRF model was run for 19 summers from 2000 to 2018 configured with four different land surface schemes including CLM4, Noah-MP, Pleim-Xiu and SSiB, hereafter referred as Exp-CLM4, Exp-Noah-MP, Exp-PX and Exp-SSiB respectively. The initial and boundary conditions for the WRF model simulations were provided by the National Centers for Environmental Prediction Final (NCEP-FNL) Operational Global Analysis data. The ERA-Interim reanalysis (ERAI), the GHCN-CAMS and the CRU gridded data were used to comprehensively evaluate the WRF simulations. Compared with the reanalysis and observational data, the WRF model can reasonably reproduce the spatial patterns of summer mean 2-m temperature, precipitation, and large- scale atmospheric circulation. The simulations, however, are sensitive to the option of land surface scheme. The performance of Exp-CLM4 and Exp-SSiB are better than that of Exp-Noah-MP and Exp-PX assessed by Multivariable Integrated Evaluation (MVIE) method. To comprehensively understand the dynamic and physical mechanisms for the WRF model’s sensitivity to land surface schemes, the differences in the surface energy balance between Ave-CLM4-SSiB (the ensemble average of Exp-CLM4 and Exp-SSiB) and Ave-NoanMP-PX (the ensemble average of Exp-Noah-MP and Exp-PX) are analyzed in detail. The results demonstrate that the sensible and latent heat fluxes are respectively lower by 30.42 W·m−2 and higher by 14.86 W·m−2 in Ave-CLM4-SSiB than that in Ave-NoahMP-PX. As a result, large differences in geopotential height occur over the simulation domain. The simulated wind fields are subsequently influenced by the geostrophic adjustment process, thus the simulations of 2-m temperature, surface skin temperature and precipitation are respectively lower by about 2.08 ℃, 2.23 ℃ and 18.56 mm·month−1 in Ave-CLM4-SSiB than that in Ave-NoahMP-PX over Central Asia continent.

Evaluating the Spatial Distribution of WRF-Simulated Rainfall, 2-m Air Temperature, and 2-m Relative Humidity over the Urban Region of Bangalore, India

The present study evaluates the skill of the Weather Research and Forecasting (WRF) model to simulate high-resolution rainfall, 2-m air temperature (T2m), and 2-m relative humidity (RH2m) over the metropolitan city of Bangalore, India. The novelty of the present study is that the WRF model simulations were carried out for ten different rain intensities during the monsoon season and compared with in situ observations from a high-density rain gauge network (81 rain gauge stations) and automatic weather stations (AWS) located over Bangalore. Our analysis shows that the model underestimated (bias score < 1) rainfall for most (87%) of the stations, and the model accuracy in the forecasting of rainfall was more than 70% for 16% of stations in the city. The RMSE values ranged between 18 and 28 mm/day for most of the rainfall events. Our analysis also found that the underestimation of the convective available potential energy (CAPE < 2000 J/kg) may be a possible reason for the simulation of low-intensity rainfall (< 10 mm/day) in most of the stations in Bangalore. In the case of T2m and RH2m simulations, the model closely matched the observed values [bias: T2m (−1 °C to 1 °C), Rh2m (0–10%)] for most of the AWS, while the model showed cold (−4.5 °C) and moist bias (19%) for the industrial area of Begur station. Proper representation of the urban morphology, air pollution, and anthropogenic heat data in the WRF modeling system may improve the model skill to capture the spatial variability in rainfall, T2m, and RH2m over highly urbanized cities in India.

Modeling the spatiotemporal response of dew point temperature, air temperature and rainfall to land use land cover change over West Africa

The study validated the use of an updated MCD12Q1 MODIS Land Use Land Cover (LULC) data into Weather Research and Forecasting (WRF) model and investigated the effects of LULC change on the spatiotemporal pattern of dew point temperature (DPT), temperature, precipitation and some associated parameters over West Africa (WA). Series of WRF model simulations were carried out with 6 LULC scenarios, which include Built-up (Bu), Partial Deforest I and II (PDI/PDII), Partial Afforest (PA), Total Afforest (TA) and Total Deforest (TD). MCD12Q1 LULC data was integrated into WRF model to carry out eight simulations from May–September, 2012 at 12 km horizontal resolution over WA. The integration of updated MODIS LU data into WRF model showed improvement with lesser RMSE. The BU and TD scenario generally decreases dew point temperature while the areas with remarkable decrease (increase) in dew point temperature also have a decrease (increase) in evapotranspiration and an increase (decrease) in Sensible Heat (SH). Increased SH could be a factor for the increased precipitation over the urbanized area. All afforestation options decreased the temperature due to weakening of the SH. Afforestation of the Sahel led to an increase in rainfall, which is attributed to increase in ET. Deforestation of the Guinea zone (PDI/PDII) reduced the precipitation in Sahel and Sahel–Sahara interface and the entire area. Only the TA scenario increased precipitation over the Sahel–Sahara interface due to increased ET. The effects of LULC change on precipitation are complex as more in-depth analysis of the effects on major features of the general circulation of WA is recommended for future research.