Ben Yang

A Modeling Study of Irrigation Effects on Surface Fluxes and Land–Air–Cloud Interactions in the Southern Great Plains

AbstractIn this study, the authors incorporate an operational-like irrigation scheme into the Noah land surface model as part of the Weather Research and Forecasting Model (WRF). A series of simulations, with and without irrigation, is conducted over the Southern Great Plains (SGP) for an extremely dry (2006) and wet (2007) year. The results show that including irrigation reduces model bias in soil moisture and surface latent heat (LH) and sensible heat (SH) fluxes, especially during a dry year. Irrigation adds additional water to the surface, leading to changes in the planetary boundary layer. The increase in soil moisture leads to increases in the surface evapotranspiration and near-surface specific humidity but decreases in the SH and surface temperature. Those changes are local and occur during daytime. There is an irrigation-induced decrease in both the lifting condensation level (ZLCL) and mixed-layer depth. The decrease in ZLCL is larger than the decrease in mixed-layer depth, suggesting an increas...

Simulation of urban climate with high-resolution WRF model: A case study in Nanjing, China

In this study, urban climate in Nanjing of eastern China is simulated using 1-km resolution Weather Research and Forecasting (WRF) model coupled with a single-layer Urban Canopy Model. Based on the 10-summer simulation results from 2000 to 2009 we find that the WRF model is capable of capturing the high-resolution features of urban climate over Nanjing area. Although WRF underestimates the total precipitation amount, the model performs well in simulating the surface air temperature, relative humidity, and precipitation frequency and inter-annual variability. We find that extremely hot events occur most frequently in urban area, with daily maximum (minimum) temperature exceeding 36°C (28°C) in around 40% (32%) of days. Urban Heat Island (UHI) effect at surface is more evident during nighttime than daytime, with 20% of cases the UHI intensity above 2.5°C at night. However, The UHI affects the vertical structure of Planet Boundary Layer (PBL) more deeply during daytime than nighttime. Net gain for latent heat and net radiation is larger over urban than rural surface during daytime. Correspondingly, net loss of sensible heat and ground heat are larger over urban surface resulting from warmer urban skin. Because of different diurnal characteristics of urban-rural differences in the latent heat, ground heat and other energy fluxes, the near surface UHI intensity exhibits a very complex diurnal feature. UHI effect is stronger in days with less cloud or lower wind speed. Model results reveal a larger precipitation frequency over urban area, mainly contributed by the light rain events (< 10 mm d−1). Consistent with satellite dataset, around 10–20% more precipitation occurs in urban than rural area at afternoon induced by more unstable urban PBL, which induces a strong vertical atmospheric mixing and upward moisture transport. A significant enhancement of precipitation is found in the downwind region of urban in our simulations in the afternoon.

Calibration of a convective parameterization scheme in the WRF model and its impact on the simulation of East Asian summer monsoon precipitation

Reasonably modeling the magnitude, south–north gradient and seasonal propagation of precipitation associated with the East Asian summer monsoon (EASM) is a challenging task in the climate community. In this study we calibrate five key parameters in the Kain–Fritsch convection scheme in the WRF model using an efficient importance-sampling algorithm to improve the EASM simulation. We also examine the impacts of the improved EASM precipitation on other physical process. Our results suggest similar model sensitivity and values of optimized parameters across years with different EASM intensities. By applying the optimal parameters, the simulated precipitation and surface energy features are generally improved. The parameters related to downdraft, entrainment coefficients and CAPE consumption time (CCT) can most sensitively affect the precipitation and atmospheric features. Larger downdraft coefficient or CCT decrease the heavy rainfall frequency, while larger entrainment coefficient delays the convection development but build up more potential for heavy rainfall events, causing a possible northward shift of rainfall distribution. The CCT is the most sensitive parameter over wet region and the downdraft parameter plays more important roles over drier northern region. Long-term simulations confirm that by using the optimized parameters the precipitation distributions are better simulated in both weak and strong EASM years. Due to more reasonable simulated precipitation condensational heating, the monsoon circulations are also improved. By using the optimized parameters the biases in the retreating (beginning) of Mei-yu (northern China rainfall) simulated by the standard WRF model are evidently reduced and the seasonal and sub-seasonal variations of the monsoon precipitation are remarkably improved.

Evaluation of the summer precipitation over China simulated by BCC_CSM model with different horizontal resolutions during the recent half century

The performance of Beijing Climate Center climate system model with different horizontal resolutions (BCC_CSM1.1 with coarse resolution and BCC_CSM1.1 m with fine resolution) in simulating the summer precipitation over China during the recent half century is evaluated, and the possible underlying physical mechanisms related to the model biases are also further analyzed and discussed. Results show that increasing horizontal resolution does improve the summer precipitation simulation over most part of China especially in western China due to the more realistic description of the topography. However, the summer precipitation amount (PA) over eastern China characterized by monsoonal climates is much more underestimated in the finer resolution model. It is also noted that the improvement (deterioration) of the summer PA over western (eastern) China in BCC_CSM1.1 m model is mainly due to the better (worse) simulation of the moderate and heavy precipitation relative to BCC_CSM1.1 model. In addition, increasing model horizontal resolution can significantly improve the convective precipitation simulation especially over western China but shows very limited improvement in the large-scale precipitation simulation. The much more underestimated summer PA over eastern China in BCC_CSM1.1 m model relative to BCC_CSM1.1 model is due to the significantly reduced positive biases of the convective PA but few changes in the negative biases of the large-scale PA. Further mechanism analysis suggests that both the underestimated land-sea thermal contrast and the overestimated Western Pacific subtropical high result in much less northeastward water vapor transport and summer PA over eastern China in BCC_CSM1.1 m model than in BCC_CSM1.1 model.

Parametric Sensitivity Analysis for the Asian Summer Monsoon Precipitation Simulation in the Beijing Climate Center AGCM, Version 2.1

AbstractIn this study, the authors apply an efficient sampling approach and conduct a large number of simulations to explore the sensitivity of the simulated Asian summer monsoon (ASM) precipitation, including the climatological state and interannual variability, to eight parameters related to the cloud and precipitation processes in the Beijing Climate Center AGCM, version 2.1 (BCC_AGCM2.1). The results herein show that BCC_AGCM2.1 has large biases in simulating the ASM precipitation. The precipitation efficiency and evaporation coefficient for deep convection are the most sensitive parameters in simulating the ASM precipitation. With optimal parameter values, the simulated precipitation climatology could be remarkably improved, including increased precipitation over the equatorial Indian Ocean, suppressed precipitation over the Philippine Sea, and more realistic mei-yu distribution over eastern China. The ASM precipitation interannual variability is further analyzed, with a focus on the ENSO impacts. It...

A new approach to modeling aerosol effects on East Asian climate: Parametric uncertainties associated with emissions, cloud microphysics, and their interactions

In this study, we adopt a parametric sensitivity analysis framework that integrates the quasi-Monte Carlo parameter sampling approach and a surrogate model to examine aerosol effects on the East Asian Monsoon climate simulated in the Community Atmosphere Model (CAM5). A total number of 256 CAM5 simulations are conducted to quantify the model responses to the uncertain parameters associated with cloud microphysics parameterizations and aerosol (e.g., sulfate, black carbon (BC), and dust) emission factors and their interactions. Results show that the interaction terms among parameters are important for quantifying the sensitivity of fields of interest, especially precipitation, to the parameters. The relative importance of cloud microphysics parameters and emission factors (strength) depends on evaluation metrics or the model fields we focused on, and the presence of uncertainty in cloud microphysics imposes an additional challenge in quantifying the impact of aerosols on cloud and climate. Due to their different optical and microphysical properties and spatial distributions, sulfate, BC, and dust aerosols have very different impacts on East Asian Monsoon through aerosol-cloud-radiation interactions. The climatic effects of aerosol do not always have a monotonic response to the change of emission factors. The spatial patterns of both sign and magnitude of aerosol-induced changes in radiative fluxes, cloud, and precipitation could be different, depending on the aerosol types, when parameters are sampled in different ranges of values. We also identify the different cloud microphysical parameters that show the most significant impact on climatic effect induced by sulfate, BC, and dust, respectively, in East Asia.

An overview of mineral dust modeling over East Asia

East Asian dust (EAD) exerts considerable impacts on the energy balance and climate/climate change of the earth system through its influence on solar and terrestrial radiation, cloud properties, and precipitation efficiency. Providing an accurate description of the life cycle and climate effects of EAD is therefore critical to better understanding of climate change and socioeconomic development in East Asia and even worldwide. Dust modeling has undergone substantial development since the late 1990s, associated with improved understanding of the role of EAD in the earth system. Here, we review the achievements and progress made in recent decades in terms of dust modeling research, including dust emissions, long-range transport, radiative forcing (RF), and climate effects of dust particles over East Asia. Numerous efforts in dust/EAD modeling have been directed towards furnishing more sophisticated physical and chemical processes into the models on higher spatial resolutions. Meanwhile, more systematic observations and more advanced retrieval methods for instruments that address EAD related science issues have made it possible to evaluate model results and quantify the role of EAD in the earth system, and to further reduce the uncertainties in EAD simulations. Though much progress has been made, large discrepancies and knowledge gaps still exist among EAD simulations. The deficiencies and limitations that pertain to the performance of the EAD simulations referred to in the present study are also discussed.

Climatic effects of irrigation over the Huang-Huai-Hai Plain in China simulated by the weather research and forecasting model

The climatic effects of irrigation over the Huang-Huai-Hai Plain (3HP) in China are investigated by using the weather research and forecasting model coupled with an operational-like irrigation scheme. Multiple numerical experiments with irrigation off/on during spring, summer, and both spring and summer are conducted. Results show that the warm bias in surface temperature and dry bias in soil moisture are reduced over the 3HP region during the growing seasons by considering the irrigation in the model. The air temperature during nongrowing seasons is also affected by irrigation because of the persistent effects of soil moisture on land-air energy exchanges and ground heat storage. Irrigation can induce significant cooling in the planetary boundary layer (PBL) during the growing seasons and lead to a relatively wet PBL with increased low-level clouds during spring but a relatively dry condition in summer. Further analyses indicate that irrigation leads to increased summer precipitation over the Yangtze River Basin and decreased summer precipitation in southern and northern China. These responses are associated with the changes in the large-scale circulation induced by irrigation. Irrigation tends to cool the atmosphere and forces a possible southward shift of the upper level jet that can further affect the precipitation distribution. Our model results suggest that in addition to local-scale processes, large-scale impacts should also be considered when studying the precipitation response to irrigation over East Asia.

Assessing Impacts of PBL and Surface Layer Schemes in Simulating the Surface–Atmosphere Interactions and Precipitation over the Tropical Ocean Using Observations from AMIE/DYNAMO

AbstractAccuracy of turbulence parameterization in representing planetary boundary layer (PBL) processes and surface–atmosphere interactions in climate models is critical for predicting the initiation and development of clouds. This study 1) evaluates WRF Model–simulated spatial patterns and vertical profiles of atmospheric variables at various spatial resolutions and with different PBL, surface layer, and shallow convection schemes against measurements; 2) identifies model biases by examining the moisture tendency terms contributed by PBL and convection processes through nudging experiments; and 3) investigates the main causes of these biases by analyzing the dependence of modeled surface fluxes on PBL and surface layer schemes over the tropical ocean. The results show that PBL and surface parameterizations have surprisingly large impacts on precipitation and surface moisture fluxes over tropical oceans. All of the parameterizations tested tend to overpredict moisture in the PBL and free atmosphere and c...

Sensitivity of turbine-height wind speeds to parameters in planetary boundary-layer and surface-layer schemes in the weather research and forecasting model

We evaluate the sensitivity of simulated turbine-height wind speeds to 26 parameters within the Mellor–Yamada–Nakanishi–Niino (MYNN) planetary boundary-layer scheme and MM5 surface-layer scheme of the Weather Research and Forecasting model over an area of complex terrain. An efficient sampling algorithm and generalized linear model are used to explore the multiple-dimensional parameter space and quantify the parametric sensitivity of simulated turbine-height wind speeds. The results indicate that most of the variability in the ensemble simulations is due to parameters related to the dissipation of turbulent kinetic energy (TKE), Prandtl number, turbulent length scales, surface roughness, and the von Kármán constant. The parameter associated with the TKE dissipation rate is found to be most important, and a larger dissipation rate produces larger hub-height wind speeds. A larger Prandtl number results in smaller nighttime wind speeds. Increasing surface roughness reduces the frequencies of both extremely weak and strong airflows, implying a reduction in the variability of wind speed. All of the above parameters significantly affect the vertical profiles of wind speed and the magnitude of wind shear. The relative contributions of individual parameters are found to be dependent on both the terrain slope and atmospheric stability.