WRF V3 Research Articles

Optimization of weather forecasting for cloud cover over the European domain using the meteorological component of the Ensemble for Stochastic Integration of Atmospheric Simulations version 1.0

Abstract. We present the largest sensitivity study to date for cloud cover using the Weather Forecasting and Research model (WRF V3.7.1) on the European domain. The experiments utilize the meteorological part of a large-ensemble framework, ESIAS-met (Ensemble for Stochastic Integration of Atmospheric Simulations). This work demonstrates the capability and performance of ESIAS for large-ensemble simulations and sensitivity analysis. The study takes an iterative approach by first comparing over 1000 combinations of microphysics, cumulus parameterization, planetary boundary layer (PBL) physics, surface layer physics, radiation scheme, and land surface models on six test cases. We then perform more detailed studies on the long-term and 32-member ensemble forecasting performance of select combinations. The results are compared to CM SAF (Climate Monitoring Satellite Application Facility) satellite images from EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites). The results indicate a high sensitivity of clouds to the chosen physics configuration. The combination of Goddard, WRF single moments 6 (WSM6), or CAM5.1 microphysics with MYNN3 (Mellor–Yamada Nakanishi Niino level 3) or ACM2 (Asymmetrical Convective Model version 2) PBL performed best for simulating cloud cover in Europe. For ensemble-based probabilistic simulations, the combinations of WSM6 and SBU–YLin (Stony Brook University Y. Lin) microphysics with MYNN2 and MYNN3 performed best.

Impacts of land cover changes and global warming on climate in Colombia during ENSO events

Colombia is highly vulnerable to climate change which may be intensified due to the climatic effects of regional deforestation. Here, we quantify the impact of historical (1900–2011) land cover changes (LCC) and of global warming during ENSO events (CC) on precipitation, temperature and surface energy balance components by running the Weather Research and Forecasting model WRF v3.9 at 10 km resolution. We find that historical anthropogenic CC causes a mean temperature increase of 0.77 ± 0.02 °C in Colombia, which is more pronounced in high altitudes. Precipitation is enhanced by 0.98 ± 0.30 mm/day (+ 9%), particularly over forested areas and reduced at the Pacific coast. LCC imply a reduction of precipitation particularly above the Andes (− 0.48 ± 0.10 mm/day) and Caribbean Coast (− 0.67 ± 0.12 mm/day), where LCC effects dampen CC effects by 24% and 72%, respectively. La Niña tends to intensify LCC and CC effects in the Andes but dampens them at the Coast, roughly by a factor of two compared to El Niño impacts in both regions. At the subregional level, LCC and CC can have impacts of similar magnitude on precipitation highlighting the need to precisely account for both drivers in hydroclimatic assessments. Contrary to almost all observations and similar simulations with climate models, WRF simulates a cooling bias after historical deforestation in Colombia, even with alternative WRF land surface models. We identify two main sources of biases in the default WRF parametrization to explain this inaccuracy: (1) surface shortwave radiation reflected after deforestation is overestimated; (2) associated evapotranspiration loss is underestimated. Improved model representation and validation of tropical vegetation properties are necessary to provide more robust and confident projections.

Wind Power Potential in Highlands of the Bolivian Andes: A Numerical Approach

Wind resource assessment is a key factor for the development and implementation of wind farms with the purpose of generating green, eco-friendly and clean electricity. The Bolivian Andes, as a large dry region, represents an important source of renewable energy. However, the altitude and high wind energy resources of the Bolivian Andes require further knowledge and understanding of the wind energy resources. In this study, the GWA have been used to determine the total area available to install wind farms considering the protected areas, roads, cities and transmission lines. In addition, the Weather Research and Forecasting (WRF v3.8.1) model is employed to complement the results of the GWA based on the validation of WRF simulations with measurements from Qollpana wind farm. The main purpose is to estimate the wind power potential along the Bolivian Andes and its variability in time. The wind power simulations have been compared with the power generated by the Qollpana wind farm to verify the WRF’s performance. The wind power potential in the highlands of the Bolivian Andes could reach between 225 (WRF) and 277 (GWA) GW, distributed mainly over the Western and Eastern Cordillera of the Altiplano.

Evaluating long‐term One‐Way Atmosphere‐Hydrology simulations and the impacts of Two‐Way coupling in four mountain watersheds

AbstractJoint hydrologic‐atmospheric model frameworks offer novel insights into the terrestrial hydrologic cycle and the potential for improved predictive capabilities for stream discharge and other hydrologic fluxes. In this study, we examine both one‐ and two‐way coupled integrations of the Weather Research and Forecasting (WRF v3.8.1) atmospheric and WRF‐Hydro (v5.0) hydrologic models for four 1000–2000 km2 snow‐dominated mountain watersheds (1500–2100 m mean elevation) in Idaho's Rocky Mountains. In watersheds where anthropogenic withdrawals are minimal (3 of 4 watersheds), we simulate stream discharge with high confidence (KGE > 0.63) for a 20 year period in the uncoupled scenarios, and find that WRF winter precipitation accumulations have less than 15% average error for all but two of the fourteen comparison NRCS Snotel sites. However, annual streamflow biases are highly correlated (r2 > 0.8 in some cases) with the annual errors in WRF cold‐season precipitation, suggesting that process representation of winter orographic precipitation limits hydrologic predictability. In the second part of the study, we evaluate the potential for ‘two‐way’ model coupling to influence hydrologic predictability by examining a 2 month case‐study period with active spring season convective precipitation. We quantify the impacts of resolving hillslope‐scale soil water redistribution on the ABL, and find that while resolving overland and saturated subsurface soil moisture flow influences soil moisture distributions and surface energy fluxes, the impact on precipitation is non‐systematic, as precipitation is generally atmospherically controlled during the study period. Consequently, future efforts should focus on improving winter orographic process representation, as streamflow is highly sensitive to errors in these processes.

Impact of physical parameterizations on wind simulation with WRF V3.9.1.1 under stable conditions at PBL gray-zone resolution: a case study over the coastal regions of North China

Impact of physical parameterizations on wind simulation with WRF V3.9.1.1 under stable conditions at PBL gray-zone resolution: a case study over the coastal regions of North China

A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry-meteorology feedbacks on air quality.

The two-way coupled Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model has been developed to more realistically represent the atmosphere by accounting for complex chemistry-meteorology feedbacks. In this study, we present a comparative analysis of two-way (with consideration of both aerosol direct and indirect effects) and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US. Long-term (5 years from 2008 to 2012) simulations using WRF-CMAQ with both offline and two-way coupling modes are carried out with anthropogenic emissions based on multiple years of the U.S. National Emission Inventory and chemical initial and boundary conditions derived from an advanced Earth system model (i.e., a modified version of the Community Earth System Model/Community Atmospheric Model). The comprehensive model evaluations show that both two-way WRF-CMAQ and WRF-only simulations perform well for major meteorological variables such as temperature at 2 m, relative humidity at 2 m, wind speed at 10 m, precipitation (except for against the National Climatic Data Center data), and shortwave and longwave radiation. Both two-way and offline CMAQ also show good performance for ozone (O3) and fine particulate matter (PM2.5). Due to the consideration of aerosol direct and indirect effects, two-way WRF-CMAQ shows improved performance over offline coupled WRF and CMAQ in terms of spatiotemporal distributions and statistics, especially for radiation, cloud forcing, O3, sulfate, nitrate, ammonium, elemental carbon, tropospheric O3 residual, and column nitrogen dioxide (NO2). For example, the mean biases have been reduced by more than 10 W m-2 for shortwave radiation and cloud radiative forcing and by more than 2 ppb for max 8 h O3. However, relatively large biases still exist for cloud predictions, some PM2.5 species, and PM10 that warrant follow-up studies to better understand those issues. The impacts of chemistry-meteorological feedbacks are found to play important roles in affecting regional air quality in the US by reducing domain-average concentrations of carbon monoxide (CO), O3, nitrogen oxide (NO x ), volatile organic compounds (VOCs), and PM2.5 by 3.1% (up to 27.8%), 4.2% (up to 16.2%), 6.6% (up to 50.9%), 5.8% (up to 46.6%), and 8.6% (up to 49.1%), respectively, mainly due to reduced radiation, temperature, and wind speed. The overall performance of the two-way coupled WRF-CMAQ model achieved in this work is generally good or satisfactory and the improved performance for two-way coupled WRF-CMAQ should be considered along with other factors in developing future model applications to inform policy making.

Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements

Abstract. Atmospheric pollution has many profound effects on human health, ecosystems, and the climate. Of concern are high concentrations and deposition of reactive nitrogen (Nr) species, especially of reduced N (gaseous NH3, particulate NH4+). Atmospheric chemistry and transport models (ACTMs) are crucial to understanding sources and impacts of Nr chemistry and its potential mitigation. Here we undertake the first evaluation of the global version of the EMEP MSC-W ACTM driven by WRF meteorology (1∘×1∘ resolution), with a focus on surface concentrations and wet deposition of N and S species relevant to investigation of atmospheric Nr and secondary inorganic aerosol (SIA). The model–measurement comparison is conducted both spatially and temporally, covering 10 monitoring networks worldwide. Model simulations for 2010 compared use of both HTAP and ECLIPSEE (ECLIPSE annual total with EDGAR monthly profile) emissions inventories; those for 2015 used ECLIPSEE only. Simulations of primary pollutants are somewhat sensitive to the choice of inventory in places where regional differences in primary emissions between the two inventories are apparent (e.g. China) but are much less sensitive for secondary components. For example, the difference in modelled global annual mean surface NH3 concentration using the two 2010 inventories is 18 % (HTAP: 0.26 µg m−3; ECLIPSEE: 0.31 µg m−3) but is only 3.5 % for NH4+ (HTAP: 0.316 µg m−3; ECLIPSEE: 0.305 µg m−3). Comparisons of 2010 and 2015 surface concentrations between the model and measurements demonstrate that the model captures the overall spatial and seasonal variations well for the major inorganic pollutants NH3, NO2, SO2, HNO3, NH4+, NO3-, and SO42- and their wet deposition in East Asia, Southeast Asia, Europe, and North America. The model shows better correlations with annual average measurements for networks in Southeast Asia (mean R for seven species: R7‾=0.73), Europe (R7‾=0.67), and North America (R7‾=0.63) than in East Asia (R5‾=0.35) (data for 2015), which suggests potential issues with the measurements in the latter network. Temporally, both model and measurements agree on higher NH3 concentrations in spring and summer and lower concentrations in winter. The model slightly underestimates annual total precipitation measurements (by 13 %–45 %) but agrees well with the spatial variations in precipitation in all four world regions (0.65–0.94 R range). High correlations between measured and modelled NH4+ precipitation concentrations are also observed in all regions except East Asia. For annual total wet deposition of reduced N, the greatest consistency is in North America (0.75–0.82 R range), followed by Southeast Asia (R=0.68) and Europe (R=0.61). Model–measurement bias varies between species in different networks; for example, bias for NH4+ and NO3- is largest in Europe and North America and smallest in East Asia and Southeast Asia. The greater uniformity in spatial correlations than in biases suggests that the major driver of model–measurement discrepancies (aside from differing spatial representativeness and uncertainties and biases in measurements) are shortcomings in absolute emissions rather than in modelling the atmospheric processes. The comprehensive evaluations presented in this study support the application of this model framework for global analysis of current and potential future budgets and deposition of Nr and SIA.

Seasonal and diurnal performance of daily forecasts with WRF V3.8.1 over the United Arab Emirates

Abstract. Effective numerical weather forecasting is vital in arid regions like the United Arab Emirates (UAE) where extreme events like heat waves, flash floods, and dust storms are severe. Hence, accurate forecasting of quantities like surface temperatures and humidity is very important. To date, there have been few seasonal-to-annual scale verification studies with WRF at high spatial and temporal resolution. This study employs a convection-permitting scale (2.7 km grid scale) simulation with WRF with Noah-MP, in daily forecast mode, from 1 January to 30 November 2015. WRF was verified using measurements of 2 m air temperature (T2 m), 2 m dew point (TD2 m), and 10 m wind speed (UV10 m) from 48 UAE WMO-compliant surface weather stations. Analysis was made of seasonal and diurnal performance within the desert, marine, and mountain regions of the UAE. Results show that WRF represents temperature (T2 m) quite adequately during the daytime with biases ≤+1 ∘C. There is, however, a nocturnal cold bias (−1 to −4 ∘C), which increases during hotter months in the desert and mountain regions. The marine region has the smallest T2 m biases (≤-0.75 ∘C). WRF performs well regarding TD2 m, with mean biases mostly ≤ 1 ∘C. TD2 m over the marine region is overestimated, though (0.75–1 ∘C), and nocturnal mountain TD2 m is underestimated (∼-2 ∘C). UV10 m performance on land still needs improvement, and biases can occasionally be large (1–2 m s−1). This performance tends to worsen during the hot months, particularly inland with peak biases reaching ∼ 3 m s−1. UV10 m is better simulated in the marine region (bias ≤ 1 m s−1). There is an apparent relationship between T2 m bias and UV10 m bias, which may indicate issues in simulation of the daytime sea breeze. TD2 m biases tend to be more independent. Studies such as these are vital for accurate assessment of WRF nowcasting performance and to identify model deficiencies. By combining sensitivity tests, process, and observational studies with seasonal verification, we can further improve forecasting systems for the UAE.

Implementation of a synthetic inflow turbulence generator in idealised WRF v3.6.1 large eddy simulations under neutral atmospheric conditions

Abstract. A synthetic inflow turbulence generator was implemented in the idealised Weather Research and Forecasting large eddy simulation (WRF-LES v3.6.1) model under neutral atmospheric conditions. This method is based on an exponential correlation function and generates a series of two-dimensional slices of data which are correlated both in space and in time. These data satisfy a spectrum with a near “-5/3” inertial subrange, suggesting its excellent capability for high Reynolds number atmospheric flows. It is more computationally efficient than other synthetic turbulence generation approaches, such as three-dimensional digital filter methods. A WRF-LES simulation with periodic boundary conditions was conducted to provide prior mean profiles of first and second moments of turbulence for the synthetic turbulence generation method, and the results of the periodic case were also used to evaluate the inflow case. The inflow case generated similar turbulence structures to those of the periodic case after a short adjustment distance. The inflow case yielded a mean velocity profile and second-moment profiles that agreed well with those generated using periodic boundary conditions, after a short adjustment distance. For the range of the integral length scales of the inflow turbulence (±40 %), its effect on the mean velocity profiles is negligible, whereas its influence on the second-moment profiles is more visible, in particular for the smallest integral length scales, e.g. those with the friction velocity of less than 4 % error of the reference data at x/H=7. This implementation enables a WRF-LES simulation of a horizontally inhomogeneous case with non-repeated surface land-use patterns and can be extended so as to conduct a multi-scale seamless nesting simulation from a meso-scale domain with a kilometre-scale resolution down to LES domains with metre-scale resolutions.

Towards the closure of momentum budget analyses in the WRF (v3.8.1) model

Abstract. Budget analysis of a tendency equation is widely utilized in numerical studies to quantify different physical processes in a simulated system. While such analysis is often post-processed when the output is made available, it is well acknowledged that the closure of a budget is difficult to achieve without temporal and/or spatial averaging. Nevertheless, the development of errors in such calculations has not been systematically investigated. In this study, an inline budget retrieval method is first developed in the WRF v3.8.1 model and tested on a 2D idealized slantwise convection case with a focus on the momentum equations. This method extracts all the budget terms following the model solver, which gives a high accuracy, with a residual term always less than 0.1 % of the tendency term. Then, taking the inline values as truth, several offline budget analyses with different commonly used simplifications are performed to investigate how they may affect the accuracy of the estimation of individual terms and the resultant residual. These assumptions include using a lower-order advection operator than the one used in the model, neglecting grid staggering, or following a mathematically equivalent but transformed format of the governing equations. Errors in these post-processed analyses are found mostly over the area where the dynamics are the most active, thus impairing the subsequent physical interpretation. A maximum 99th percentile residual can reach >50 % of the concurrent tendency term, indicating the danger of neglecting the residual term as done in many budget studies. This work provides general guidance not only for budget diagnoses with the WRF model but also for minimizing the errors in post-processed budget calculations.

Traffic-induced multicomponent ultrafine particle microphysics in the WRF v3.6.1 large eddy simulation model: General behaviour from idealised scenarios at the neighbourhood-scale

Traffic is the key source of ultrafine particles (UFPs, particulate matter with a diameter less than 0.1 μm or 100 nm) in most urban areas. The traffic-generated UFPs vented out from an urban street mix with overlying ‘urban background air’ and are diluted whilst also undergoing change due to condensation/evaporation and other aerosol microphysics. Traffic-generated UFPs are comprised of a complex mixture of semi-volatile compounds (SVOCs) with volatility varying over many orders of magnitude, resulting in size-dependent particle composition. This study coupled the multicomponent microphysics (involving condensation/evaporation) of UFPs with the WRF v3.6.1 (Weather Research and Forecasting) large eddy simulation model (i.e. WRF-LES-UFP), and used this modelling system to investigate the general behaviour of UFPs on the neighbourhood scale (10-1000 m; transport times of few minutes) for idealised scenarios. The model captures the horizontal dispersion of UFPs downwind into the neighbourhood scale and vertical mixing with urban background air. Evaporation decreases the mode size of UFPs venting into the urban boundary layer from street-level. The neighbourhood-scale evolution of UFPs is, therefore, a combination of the effects of emissions, mixing with background, and condensation/evaporation. Total UFP number concentration and total mass concentrations scale linearly with the emission rate or the background concentration, demonstrating numerical conservation of the scheme. The linearity is less pronounced for the number concentration of smaller particles (UFP diameter less than 100 nm) with respect to UFP size and concentrations of those organic compounds with a time scale comparable to the dilution time scale (in the order of minutes), reflecting the effects (altering the particle sizes) due to condensation/evaporation.

Towards a definitive historical high-resolution climate dataset for Ireland – promoting climate research in Ireland

Abstract. There is strong and constant demand from various sectors (research, industry and government) for long-term, high-resolution (both temporal and spatial), gridded climate datasets. To address this demand, the Irish Centre for High-End Computing (ICHEC) has recently performed two high-resolution simulations of the Irish climate, utilising the Regional Climate Models (RCMs) COSMO-CLM5 and WRF v3.7.1. The datasets produced contain hourly outputs for an array of sub-surface, surface and atmospheric fields for the entire 36-year period 1981–2016. In this work, we list the climate variables that have been archived at ICHEC. We present preliminary uncertainty estimates (error, standard deviation, mean absolute error) based on Met Éireann station observations, for several of the more commonly used variables: 2 m temperature, 10 m wind speeds and mean sea level pressure at the hourly time scale; and precipitation at hourly and daily time scales. Additionally, analyses of 10 cm soil temperatures, CAPE 3 km, Showalter index and surface lifted index are presented.

Differences of atmospheric boundary layer characteristics between pre-monsoon and monsoon period over the Erhai Lake

The differences in planetary boundary layer characteristics, in particular atmospheric boundary layer height (ABLH), humidity, and local circulations in pre-monsoon and monsoon period over the Erhai Lake, were simulated by the lake-atmosphere coupled model WRF v3.7.1. No lake simulations were also conducted to investigate lake effects over complex topography. During pre-monsoon period, local circulation was fully developed under weak synoptic system. The ABLH ran up to 2300 m or so. During monsoon period, temperature difference between land and lake became smaller, resulting in weaker local circulations. The height of circulation reduced by 500 m, and ABLH ran up to 1100 m during the day. Enhanced soil moisture and low surface temperature due to monsoon rainfalls in July could be the main reason for the slightly lower ABLH over the Erhai Lake area. Specific humidity of the boundary layer increased 8.8 g kg−1 or so during monsoon period. The Erhai Lake enlarged thermal contrast between valley and mountain slope in the Dali Basin. The lake reduced air temperature by 2~3 °C during daytime and increased air temperature by nearly 2 °C in the evening. Due to its small roughness length and large thermal capacity, the Erhai Lake enlarged lake-land temperature difference and local wind speed. A cyclonic circulation was maintained by the combination of mountain breeze and land breeze in the south of the lake. The lake decreased air temperature, increased specific humidity, and reduced ABLH during daytime, whereas the opposite effect is presented at night.

Influence of Ice Nuclei Parameterization Schemes on the Hail Process

Ice nuclei are very important factors as they significantly affect the development and evolvement of convective clouds such as hail clouds. In this study, numerical simulations of hail processes in the Zhejiang Province were conducted using a mesoscale numerical model (WRF v3.4). The effects of six ice nuclei parameterization schemes on the macroscopic and microscopic structures of hail clouds were compared. The effect of the ice nuclei concentration on ground hailfall is stronger than that on ground rainfall. There were significant spatiotemporal, intensity, and distribution differences in hailfall. Changes in the ice nuclei concentration caused different changes in hydrometeors and directly affected the ice crystals, and, hence, the spatiotemporal distribution of other hydrometeors and the thermodynamic structure of clouds. An increased ice nuclei concentration raises the initial concentration of ice crystals with higher mixing ratio. In the developing and early maturation stages of hail cloud, a larger number of ice crystals competed for water vapor with increasing ice nuclei concentration. This effect prevents ice crystals from maturing into snow particles and inhibits the formation and growth of hail embryos. During later maturation stages, updraft in the cloud intensified and more supercooled water was transported above the 0°C level, benefitting the production and growth of hail particles. An increased ice nuclei concentration therefore favors the formation of hail.

Multi-year downscaling application of two-way coupled WRF v3.4 and CMAQ v5.0.2 over east Asia for regional climate and air quality modeling: model evaluation and aerosol direct effects

Abstract. In this study, a regional coupled climate–chemistry modeling system using the dynamical downscaling technique was established by linking the global Community Earth System Model (CESM) and the regional two-way coupled Weather Research and Forecasting – Community Multi-scale Air Quality (WRF-CMAQ) model for the purpose of comprehensive assessments of regional climate change and air quality and their interactions within one modeling framework. The modeling system was applied over east Asia for a multi-year climatological application during 2006–2010, driven with CESM downscaling data under Representative Concentration Pathways 4.5 (RCP4.5), along with a short-term air quality application in representative months in 2013 that was driven with a reanalysis dataset. A comprehensive model evaluation was conducted against observations from surface networks and satellite observations to assess the model's performance. This study presents the first application and evaluation of the two-way coupled WRF-CMAQ model for climatological simulations using the dynamical downscaling technique. The model was able to satisfactorily predict major meteorological variables. The improved statistical performance for the 2 m temperature (T2) in this study (with a mean bias of −0.6 °C) compared with the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-models might be related to the use of the regional model WRF and the bias-correction technique applied for CESM downscaling. The model showed good ability to predict PM2. 5 in winter (with a normalized mean bias (NMB) of 6.4 % in 2013) and O3 in summer (with an NMB of 18.2 % in 2013) in terms of statistical performance and spatial distributions. Compared with global models that tend to underpredict PM2. 5 concentrations in China, WRF-CMAQ was able to capture the high PM2. 5 concentrations in urban areas. In general, the two-way coupled WRF-CMAQ model performed well for both climatological and air quality applications. The coupled modeling system with direct aerosol feedbacks predicted aerosol optical depth relatively well and significantly reduced the overprediction in downward shortwave radiation at the surface (SWDOWN) over polluted regions in China. The performance of cloud variables was not as good as other meteorological variables, and underpredictions of cloud fraction resulted in overpredictions of SWDOWN and underpredictions of shortwave and longwave cloud forcing. The importance of climate–chemistry interactions was demonstrated via the impacts of aerosol direct effects on climate and air quality. The aerosol effects on climate and air quality in east Asia (e.g., SWDOWN and T2 decreased by 21.8 W m−2 and 0.45 °C, respectively, and most pollutant concentrations increased by 4.8–9.5 % in January over China's major cities) were more significant than in other regions because of higher aerosol loadings that resulted from severe regional pollution, which indicates the need for applying online-coupled models over east Asia for regional climate and air quality modeling and to study the important climate–chemistry interactions. This work established a baseline for WRF-CMAQ simulations for a future period under the RCP4.5 climate scenario, which will be presented in a future paper.

Examination of physical processes of convective cell evolved from a MCS — Using a different model initialization

The present study is focused on examination of the physical processes of convective cell evolved from a MCS occurred on 4 November 2011 over Genoa, Italy. The Quantitative Precipitation Forecasts (QPF) have been performed using WRF v3.6 model under different configurations and cloud permitting simulations. The results indicate underestimation of the amount of precipitation and spatial displacement of the area with a peak 24-h accumulated rainfall in (mm). Our main objective in the research is to test the cloud model ability and performance in simulation of this particular case. For that purpose a set of sensitivity experiments under different model initializations and initial data have been conducted. The results also indicate that the merging process apparently alters the physical processes through low- and middle-level forcing, increasing cloud depth, and enhancing convection. The examination of the microphysical process simulated by the model indicates that dominant production terms are the accretion of rain by graupel and snow, probabilistic freezing of rain to form graupel and dry and wet growth of graupel. Experiment under WRF v3.6 model initialization has shown some advantage in simulation of the physical processes responsible for production and initiation of heavy rainfall compared to other model runs. Most of the precipitation came from ice-phase particles-via accretion processes and the graupel melting at temperature T0 ≥ 0°C. The rainfall intensity and accumulated rainfall calculated by the model closely reflect the amount of rainfall recorded. Thus, the main benefit is to better resolve convective showers or storms which, in extreme cases, can give rise to major flooding events. In such a way, this model may become major contributor to improvements in weather analysis and small-scale atmospheric predictions and early warnings of such subscale processes.

WRF model evaluation for the urban heat island assessment under varying land use/land cover and reference site conditions

Urban heat island effect in Delhi has been assessed using Weather Research and Forecasting (WRF v3.5) coupled with urban canopy model (UCM) focusing on air temperature and surface skin temperature. The estimated heat island intensities for different land use/land cover (LULC) have been compared with those derived from in situ and satellite observations. The model performs reasonably well for urban heat island intensity (UHI) estimation and is able to reproduce trend of UHI for urban areas. There is a significant improvement in model performance with inclusion of UCM which results in reduction in root mean-squared errors (RMSE) for temperatures from 1.63 °C (2.89 °C) to 1.13 °C (2.75 °C) for urban (non-urban) areas. Modification of LULC also improves performance for non-urban areas. High UHI zones and top 3 hotspots are captured well by the model. The relevance of selecting a reference point at the periphery of the city away from populated and built-up areas for UHI estimation is examined in the context of rapidly growing cities where rural areas are transforming fast into built-up areas, and reference site may not be appropriate for future years. UHI estimated by WRF model (with and without UCM) with respect to reference rural site compares well with the UHI based on observed in situ data. An alternative methodology is explored using a green area with minimum temperature within the city as a reference site. This alternative methodology works well with observed UHIs and WRF-UCM-simulated UHIs but has poor performance for WRF-simulated UHIs. It is concluded that WRF model can be applied for UHI estimation with classical methodology based on rural reference site. In general, many times WRF model performs satisfactorily, though WRF-UCM always shows a better performance. Hence, inclusion of appropriate representation of urban canopies and land use–land cover is important for improving predictive capabilities of the mesoscale models.

Sea Ice Enhancements to Polar WRF*

Abstract The Polar Weather Research and Forecasting Model (Polar WRF), a polar-optimized version of the WRF Model, is developed and made available to the community by Ohio State University’s Polar Meteorology Group (PMG) as a code supplement to the WRF release from the National Center for Atmospheric Research (NCAR). While annual NCAR official releases contain polar modifications, the PMG provides very recent updates to users. PMG supplement versions up to WRF version 3.4 include modified Noah land surface model sea ice representation, allowing the specification of variable sea ice thickness and snow depth over sea ice rather than the default 3-m thickness and 0.05-m snow depth. Starting with WRF V3.5, these options are implemented by NCAR into the standard WRF release. Gridded distributions of Arctic ice thickness and snow depth over sea ice have recently become available. Their impacts are tested with PMG’s WRF V3.5-based Polar WRF in two case studies. First, 20-km-resolution model results for January 1998 are compared with observations during the Surface Heat Budget of the Arctic Ocean project. Polar WRF using analyzed thickness and snow depth fields appears to simulate January 1998 slightly better than WRF without polar settings selected. Sensitivity tests show that the simulated impacts of realistic variability in sea ice thickness and snow depth on near-surface temperature is several degrees. The 40-km resolution simulations of a second case study covering Europe and the Arctic Ocean demonstrate remote impacts of Arctic sea ice thickness on midlatitude synoptic meteorology that develop within 2 weeks during a winter 2012 blocking event.

Sensitivity of the regional European boreal climate to changes in surface properties resulting from structural vegetation perturbations

Abstract. Amplified warming at high latitudes over the past few decades has led to changes in the boreal and Arctic climate system such as structural changes in high-latitude ecosystems and soil moisture properties. These changes trigger land–atmosphere feedbacks through altered energy partitioning in response to changes in albedo and surface water fluxes. Local-scale changes in the Arctic and boreal zones may propagate to affect large-scale climatic features. In this study, MODIS land surface data are used with the Weather Research and Forecasting model (WRF V3.5.1) and Noah land surface model (LSM), in a series of experiments to investigate the sensitivity of the overlying atmosphere to perturbations in the structural vegetation in the northern European boreal ecosystem. Emphasis is placed on surface energy partitioning and near-surface atmospheric variables, and their response to observed and anticipated land cover changes. We find that perturbations simulating northward migration of evergreen needleleaf forest into tundra regions cause an increase in latent rather than sensible heat fluxes during the summer season. Shrub expansion in tundra areas has only small effects on surface fluxes. Perturbations simulating the northward migration of mixed forest across the present southern border of the boreal forest, have largely opposite effects on the summer latent heat flux, i.e., they lead to a decrease and act to moderate the overall mean regional effects of structural vegetation changes on the near-surface atmosphere.

Dynamically Downscaled High-Resolution Hydroclimate Projections for Western Canada

Abstract Accurate identification of the impact of global warming on water resources in major river systems represents a significant challenge to the understanding of climate change on the regional scale. Here, dynamically downscaled climate projections for western Canada are presented, and impacts on hydrological variables in two major river basins, the Fraser and Athabasca, are discussed. These regions are both challenging because of the complexity of the topography and important because of the economic activity occurring within them. To obtain robust projections of future conditions, and to adequately characterize the impact of natural variability, a small initial condition ensemble of independently downscaled climate projections is employed. The Community Earth System Model, version 1 (CESM1), is used to generate the ensemble, which consists of four members. Downscaling is performed using the Weather Research and Forecasting Model, version 3.4.1 (WRF V3.4.1), in a nested configuration with two domains at 30- and 10-km resolution, respectively. The entire ensemble was integrated for a historical validation period and for a mid-twenty-first-century projection period [assuming representative concentration pathway 8.5 (RCP8.5) for the future trajectory of greenhouse gases]. The projections herein are characterized by an increase in winter precipitation for the mid-twenty-first-century period, whereas net precipitation in summer is projected to decrease, due to increased evapotranspiration. In the Fraser River basin, a shift to more liquid precipitation and earlier snowmelt will likely reduce the seasonal variability of runoff, in particular the spring freshet. In the Athabasca River basin, winter precipitation and snowmelt may increase somewhat, but increasing evapotranspiration may lead to reduced streamflow in late summer.