Evaluation of the Diurnal Variation of Upper Tropospheric Humidity in Reanalysis Using Homogenized Observed Radiances from International Geostationary Weather Satellites

A near global dataset of homogenized clear-sky 6.5-μm brightness temperatures (BTs) from international geostationary (GEO) weather satellites has recently been generated and validated. In this study, these radiance measurements are used to construct the diurnal variation of upper tropospheric humidity (UTH) and to evaluate these diurnal variations simulated by five reanalysis datasets over the 45° N–45° S region. The features of the diurnal variation described by the new dataset are comparable with previous observational studies that a land–sea contrast in the diurnal variation of UTH is exhibited. Distinct diurnal variations are observed over the deep convective regions where high UTH exists. The evaluation of reanalysis datasets indicates that reanalysis systems still have considerable difficulties in capturing the observed features of the diurnal variation of UTH. All five reanalysis datasets present the largest wet biases in the afternoon when the observed UTH experiences a diurnal minimum. Reanalysis can roughly reproduce the day–night contrast of UTH but with much weaker amplitudes and later peak time over both land and ocean. Comparison of the geographical distribution of the diurnal variation shows that both ERA5 and MERRA-2 could capture the larger diurnal variations over convective regions. However, the diurnal amplitudes are widely underestimated, especially over convective land regions, while the phase biases are relatively larger over open oceans. These results suggest that some deficiencies may exist in convection and cloud parameterization schemes in reanalysis models.

Evaluation of Environmental Moisture from NWP Models with Measurements from Advanced Geostationary Satellite Imager—A Case Study

The distribution of tropospheric moisture in the environment is highly associated with storm development. Therefore, it is important to evaluate the uncertainty of moisture fields from numerical weather prediction (NWP) models for better understanding and enhancing storm prediction. With water vapor absorption band radiance measurements from the advanced imagers onboard the new generation of geostationary weather satellites, it is possible to quantitatively evaluate the environmental moisture fields from NWP models. Three NWP models—Global Forecast System (GFS), Unified Model (UM), Weather Research and Forecasting (WRF)—are evaluated with brightness temperature (BT) measurements from the three moisture channels of Advanced Himawari Imager (AHI) onboard the Himawari-8 satellite for Typhoon Linfa (2015) case. It is found that the three NWP models have similar performance for lower tropospheric moisture, and GFS has a smaller bias for middle tropospheric moisture. Besides, there is a close relationship between moisture forecasts in the environment and the tropical cyclone (TC) track forecasts in GFS, while regional WRF does not show this pattern. When the infrared and microwave sounder radiance measurements from polar orbit satellite are assimilated in regional WRF, it is clearly shown that the environment moisture fields are improved compared with that with only conventional data are assimilated.

Using a GPU to Accelerate a Longwave Radiative Transfer Model with Efficient CUDA-Based Methods

Climatic simulations rely heavily on high-performance computing. As one of the atmospheric radiative transfer models, the rapid radiative transfer model for general circulation models (RRTMG) is used to calculate the radiative transfer of electromagnetic radiation through a planetary atmosphere. Radiation physics is one of the most time-consuming physical processes, so the RRTMG presents large-scale and long-term simulation challenges to the development of efficient parallel algorithms that fit well into multicore clusters. This paper presents a method for improving the calculative efficiency of radiation physics, an RRTMG long-wave radiation scheme (RRTMG_LW) that is accelerated on a graphics processing unit (GPU). First, a GPU-based acceleration algorithm with one-dimensional domain decomposition is proposed. Then, a second acceleration algorithm with two-dimensional domain decomposition is presented. After the two algorithms were implemented in Compute Unified Device Architecture (CUDA) Fortran, a GPU version of the RRTMG_LW, namely G-RRTMG_LW, was developed. Results demonstrated that the proposed acceleration algorithms were effective and that the G-RRTMG_LW achieved a significant speedup. In the case without I/O transfer, the 2-D G-RRTMG_LW on one K40 GPU obtained a speed increase of 18.52× over the baseline performance on a single Intel Xeon E5-2680 CPU core.

Improving organic aerosol treatments in CESM/CAM5: Development, application, and evaluation

New treatments for organic aerosol (OA) formation have been added to a modified version of the CESM/CAM5 model (CESM-NCSU). These treatments include a volatility basis set treatment for the simulation of primary and secondary organic aerosols (SOAs), a simplified treatment for organic aerosol (OA) formation from glyoxal, and a parameterization representing the impact of new particle formation (NPF) of organic gases and sulfuric acid. With the inclusion of these new treatments, the concentration of oxygenated organic aerosol increases by 0.33 µg m-3 and that of primary organic aerosol (POA) decreases by 0.22 µg m-3 on global average. The decrease in POA leads to a reduction in the OA direct effect, while the increased OOA increases the OA indirect effects. Simulations with the new OA treatments show considerable improvement in simulated SOA, oxygenated organic aerosol (OOA), organic carbon (OC), total carbon (TC), and total organic aerosol (TOA), but degradation in the performance of HOA. In simulations of the current climate period, despite some deviations from observations, CESM-NCSU with the new OA treatments significantly improves the magnitude, spatial pattern, seasonal pattern of OC and TC, as well as, the speciation of TOA between POA and OOA. Sensitivity analysis reveals that the inclusion of the organic NPF treatment impacts the OA indirect effects by enhancing cloud properties. The simulated OA level and its impact on the climate system are most sensitive to choices in the enthalpy of vaporization and wet deposition of SVOCs, indicating that accurate representations of these parameters are critical for accurate OA-climate simulations.