Planetary boundary layer (PBL) schemes parameterize unresolved turbulent mixing within the PBL and free troposphere (FT). Previous studies reported that precipitation simulation over the Amazon in South America is quite sensitive to PBL schemes and the exact relationship between the turbulent mixing and precipitation processes is, however, not disentangled. In this study, regional climate simulations over the Amazon in January-February 2019 are examined at process level to understand the precipitation sensitivity to PBL scheme. The focus is on two PBL schemes, the Yonsei University (YSU) scheme, and the asymmetric convective model v2 (ACM2) scheme, which show the largest difference in the simulated precipitation. During daytime, while the FT clouds simulated by YSU dissipate, clouds simulated by ACM2 maintain because of enhanced moisture supply due to the enhanced vertical moisture relay transport process: 1) vertical mixing within PBL transports surface moisture to the PBL top, and 2) FT mixing feeds the moisture into the FT cloud deck. Due to the thick cloud deck over Amazon simulated by ACM2, surface radiative heating is reduced and consequently the convective available potential energy (CAPE) is reduced. As a result, precipitation is weaker from ACM2. Two key parameters dictating the vertical mixing are identified, p, an exponent determining boundary layer mixing and λ, a scale dictating FT mixing. Sensitivity simulations with altered p, λ, and other treatments within YSU and ACM2 confirm the precipitation sensitivity. The FT mixing in the presence of clouds appears most critical to explain the sensitivity between YSU and ACM2.

Using the Weather Research and Forecasting (WRF) model with two planetary boundary layer schemes, ACM2 and MYNN, convection-permitting model (CPM) regional climate simulations were conducted for a 6-year period at a 15-km grid spacing covering entire South America and a nested convection-permitting 3-km grid spacing covering the Peruvian central Andes region. These two CPM simulations along with a 4-km simulation covering South America produced by National Center for Atmospheric Research, three gridded global precipitation datasets, and rain gauge data in Peru and Brazil, are used to document the characteristics of precipitation and MCSs in the Peruvian central Andes region. Results show that all km-scale simulations generally capture the spatiotemporal patterns of precipitation and MCSs at both seasonal and diurnal scales, although biases exist in aspects such as precipitation intensity and MCS frequency, size, propagation speed, and associated precipitation intensity. The 3-km simulation using MYNN scheme generally outperforms the other simulations in capturing seasonal and diurnal precipitation over the mountain, while both it and the 4-km simulation demonstrate superior performance in the western Amazon Basin, based on the comparison to the gridded precipitation products and gauge data. Dynamic factors, primarily low-level jet and terrain-induced uplift, are the key drivers for precipitation and MCS genesis along the east slope of the Andes, while thermodynamic factors control the precipitation and MCS activity in the western Amazon Basin and over elevated mountainous regions. The study suggests aspects of the model needing improvement and the choice of better model configurations for future regional climate projections.

The spatiotemporal variability of latent heat flux (LE) and water vapor mixing ratio (rv) variability are not well understood due to the scale-dependent and nonlinear atmospheric energy balance responses to land surface heterogeneity. Airborne in situ and profiling Raman lidar measurements with the wavelet technique are utilized to investigate scale-dependent relationships among LE, vertical velocity (w) variance (s2w), and rv variance (s2wv) over a heterogeneous surface in the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign. Our findings reveal distinct scale distributions of LE, s2w, and s2wv at 100 m height, with a majority scale range of 120m-4km in LE, 32m-2km in s2w, and 200 m – 8 km in s2wv. The scales are classified into three scale ranges, the turbulent scale (8m–200m), large-eddy scale (200m–2km), and mesoscale (2 km–8km) to evaluate scale-resolved LE contributed by s2w and s2wv. In the large-eddy scale in Planetary Boundary Layer (PBL), 69-75% of total LE comes from 31-51% of the total sw and 39-59% of the total s2wv. Variations exist in LE, s2w, and s2wv, with a range of 1.7-11.1% of total values in monthly-mean variation, and 0.6–7.8% of total values in flight legs from July to September. These results confirm the dominant role of the large-eddy scale in the PBL in the vertical moisture transport from the surface to the PBL. This analysis complements published scale-dependent LE variations, which lack detailed scale-dependent vertical velocity and moisture information.

While the continental planetary boundary layer (PBL) structure and model capability to simulate it are relatively well understood, its structure and the ability of models to simulate it over the Southern Ocean (SO), especially in the presence of clouds, are less known. In this study, in situ soundings and remote sensing data collected from ships during two field campaigns over the SO, the Measurements of Aerosols, Radiation and Clouds over the Southern Ocean (MARCUS) and the Clouds Aerosols Precipitation Radiation and atmospheric Composition over the Southern Ocean (CAPRICORN) campaigns, and WRF simulations with different PBL schemes are examined to study the boundary layer structure over the SO, focusing particularly on the coupling status between the surface-based boundary layer and the single cloud layer above. Ten single cloud layer cases, including Dec. 1, 2017, Mar. 21-22, 2018, Mar. 23, 2018, Jan. 10, 2018 detected during MARCUS, and Feb. 17-18, 2018 detected during CAPRICORN, are examined. The cloud-boundary layer coupling over the SO for these cases can be classified into three modes: Coupled cloud-boundary layer in the presence of weak surface positive flux; Decoupled cloud-boundary layer in the presence of surface negative flux, with a very shallow surface-based PBL; and Decoupled cloud-boundary layer in the presence of single-layer high clouds and stronger surface positive flux, with thicker surface-based PBL. WRF simulations were conducted for these selected cases using different PBL schemes, including the Yonsei University (YSU) scheme with and without extra mixing and entrainment induced by cloud-top cooling (referred to as YSUtopdown when the cloud-top cooling treatment is included), the Mellor–Yamada Nakanishi and Niino (MYNN) scheme, and the MYNN scheme with the eddy-diffusivity (ED) local closure and mass flux (MF) nonlocal approach (referred to as MYNN-EDMF). For cases with the different cloud-boundary layer coupling modes, different PBL schemes provided the best consistency with observations. The MYNN-EDMF scheme is more consistent with observations than the conventional PBL schemes for the type 3 coupling mode because of the different vertical extent of local mixing and nonlocal mass flux in presence of sufficient surface flux. The YSUtopdown scheme has more consistency with observations than the YSU scheme for the type 1 coupling mode to simulate higher cloud-topped boundary layer. For the type 2 coupling mode, the different PBL schemes perform similarly.

Sources and sinks of the two most important greenhouse gases CO2 and CH4 at regional to continental scales remain poorly understood. In our previous work, the WRF-VPRM, a weather-biosphere-online-coupled model in which the biogenic CO2 fluxes are handled by the Vegetation Photosynthesis and Respiration Model (VPRM), was further developed by coupling with the CarbonTracker global CO2 simulation and incorporating optimized terrestrial CO2 flux parameterization (Hu et al., 2021; Hu et al., 2020). In this work, an enhanced version of WRF-VPRM by including CH4 (referred to as WRF-GHG hereafter) is further developed by coupling with the Copernicus Atmosphere Monitoring Service (CAMS) CH4 global simulation for the initial and boundary conditions and the WetCHARTs wetland CH4 emissions and NEI2017 anthropogenic CH4 emissions, which dominate emissions over the contiguous United States (CONUS). Yearly WRF-GHG simulations are conducted for year 2018 and 2019 over CONUS at a horizontal grid spacing of 12 km to examine the impact of 2019 abnormal mid-west precipitation on CO2 and CH4 fluxes and atmospheric concentrations, with the simulation for 2018 serving as a baseline for comparison, similarly to Yin et al (2020). Simulated CO2 and CH4 are evaluated using remotely sensed data from Total Carbon Column Observing Network (TCCON), OCO-2, TROPOMI, and in-situ measurements from the GLOBALVIEW obspack data. WRF-GHG has been shown to capture the monthly variation of column-averaged CO2 concentrations (XCO2) and episodic variations associated with frontal passages. In this work, we will show that TCCON XCH4 shows mild seasonal variation and more prominent episodic variations, which are captured by WRF-GHG. As a case study, the 2019 May flood delayed growing season in mid-west and the typical spring and summer drawdown of atmospheric CO2 by 1-3 weeks. Obspack and TROPOMI data indicate higher CH4 in the mid-west in July and August, in 2019 relative to 2018, which we hypothesize is related to the abnormal precipitation in 2019 in the region that induces more wetland CH4 emissions. The WRF-GHG model significantly underestimates CH4 concentration in mid-west in summer 2019 when the WetCHARTs wetland CH4 emissions are driven by ERA-Interim reanalysis precipitation, which is known to be underestimated. An updated WetCHARTs wetland CH4 emissions driven by the PRISM precipitation data are currently being produced at JPL, which are expected to reduce the WRF-GHG CH4 bias, as wetland fluxes are highly sensitive to inundation from precipitation.

Enhanced CO2 mole fraction bands were often observed immediately ahead of cold front during the Atmospheric Carbon and Transport (ACT)-America mission and their formation mechanism is undetermined. Improved understanding and correct simulation of these CO2 bands are needed for unbiased inverse CO2 flux estimation. Such CO2 bands are hypothesized to be related to nighttime CO2 respiration and investigated in this study using WRF-VPRM, a weather-biosphere-online-coupled model, in which the biogenic fluxes are handled by the Vegetation Photosynthesis and Respiration Model (VPRM). While the default VPRM satisfactorily parameterizes gross ecosystem exchange, its treatment of terrestrial respiration as a linear function of temperature was inadequate as respiration is a nonlinear function of temperature and also depends on the amount of biomass and soil wetness. An improved ecosystem respiration parameterization including enhanced vegetation index, a water stress factor, and a quadratic temperature dependence is incorporated into WRF-VPRM and evaluated in a year-long simulation before applied to the investigation of the frontal CO2 band on 4 August 2016. The evaluation shows that the modified WRF-VPRM increases ecosystem respiration during the growing season, and improves model skill in reproducing nighttime near-surface CO2 peaks. A nested-domain WRF-VPRM simulation is able to capture the main characteristics of the 4 August CO2 band and informs its formation mechanism. Nighttime terrestrial respiration leads to accumulation of near-surface CO2 in the region. As the cold front carrying low-CO2 air moves southeastward, and strong photosynthesis depletes CO2 further southeast of the front, a CO2 band develops immediately ahead of the front.