Evaluating a climate model's fidelity (ability to simulate observed climate) is a critical step in establishing confidence in the model's suitability for future climate projections, and in tuning climate model parameters. Model developers use their judgement in determining which trade-offs between different aspects of model fidelity are acceptable. However, little is known about the degree of consensus in these evaluations, and whether experts use the same criteria when different scientific objectives are defined. Here, we report on results from a broad community survey studying expert assessments of the relative importance of different output variables when evaluating a global atmospheric model's mean climate. We find that experts adjust their ratings of variable importance in response to the scientific objective, for instance, scientists rate surface wind stress as significantly more important for Southern Ocean climate than for the water cycle in the Asian watershed. There is greater consensus on the importance of certain variables (e.g., shortwave cloud forcing) than others (e.g., aerosol optical depth). We find few differences in expert consensus between respondents with greater or less climate modeling experience, and no statistically significant differences between the responses of climate model developers and users. The concise variable lists and community ratings reported here provide baseline descriptive data on current expert understanding of certain aspects of model evaluation, and can serve as a starting point for further investigation, as well as developing more sophisticated evaluation and scoring criteria with respect to specific scientific objectives.
This study demonstrates the two different Rossby wave train (RWT) patterns related to the developing/decaying upper atmospheric heat source over the Tibetan Plateau (TPUHS) in boreal summer. The results show that the summer TPUHS is dominated by quasi-biweekly variability, particularly from late July to mid-August when the subtropical jet steadily stays to the north of the TP. During the developing period of TPUHS events, the intensifying TPUHS corresponds to an anomalous upper-tropospheric high over the TP, which acts as the main source of a RWT that extends northeastward, via North China, the central Pacific and Alaska, to the northeastern Pacific region. This RWT breaks up while the anomalous high is temporarily replaced by an anomalous low due to the further deepened convective heating around the TPUHS peak. However, this anomalous low, though existing for only three to four days due to the counteracting dynamical effects of the persisting upper/lower divergence/convergence over the TP, acts as a new wave source to connect to an anomalous dynamical high over the Baikal region. Whilst the anomalous low is diminishing rapidly, this Baikal high becomes the main source of a new RWT, which develops eastward over the North Pacific region till around eight days after the TPUHS peak. Nevertheless, the anomaly centers along this decaying-TPUHS-related RWT mostly appear much weaker than those along the previous RWT. Therefore, their impacts on circulation and weather differ considerably from the developing to the decaying period of TPUHS events.
Changes in the form of precipitation have a considerable impact on the Arctic cryosphere and ecological system by influencing the energy balance and surface runoff. In this study, station observations and ERA-Interim data were used to analyze changes in the rainfall to precipitation ratio (RPR) in northern Canada during the spring-summer season (March-July) from 1979-2015. Our results indicate that ERA-Interim describes the spring-summer variations and trends in temperature and the RPR well. Both the spring-summer mean temperature [0.4°C-1°C (10 yr)-1] and the RPR [2%-6% (10 yr)-1] increased significantly in the Canadian Arctic Archipelago from 1979-2015. Moreover, we suggest that, aside from the contribution of climate warming, the North Atlantic Oscillation is probably another key factor influencing temporal and spatial differences in the RPR over northern Canada.
Based on high-quality data from eddy covariance measurements at the Qomolangma Monitoring and Research Station for Atmosphere and Environment (QOMS) and the Southeast Tibet Monitoring and Research Station for Environment (SETS), near-ground free convection conditions (FCCs) and their characteristics are investigated. At QOMS, strong thermal effects accompanied by lower wind speeds can easily trigger the occurrence of FCCs. The change of circulation from prevailing katabatic glacier winds to prevailing upslope winds and the oscillation of upslope winds due to cloud cover are the two main causes of decreases in wind speed at QOMS. The analysis of results from SETS shows that the most important trigger mechanism of FCCs is strong solar heating. Turbulence structural analysis using wavelet transform indicates that lower-frequency turbulence near the ground emerges from the detected FCCs both at QOMS and at SETS. It should be noted that the heterogeneous underlying surface at SETS creates large-scale turbulence during periods without the occurrence of FCCs. Regarding datasets of all seasons, the distribution of FCCs presents different characteristics during monsoonal and non-monsoonal periods.
Historical haze episodes (2013-16) in Guangzhou were examined and classified according to synoptic weather systems. Four types of weather systems were found to be unfavorable, among which "foreside of a cold front" (FC) and "sea high pressure" (SP) were the most frequent (>75% of the total). Targeted case studies were conducted based on an FC-affected event and an SP-affected event with the aim of understanding the characteristics of the contributions of source regions to fine particulate matter (PM2.5) in Guangzhou. Four kinds of contributions——namely, emissions outside Guangdong Province (super-region), emissions from the Pearl River Delta region (PRD region), emissions from Guangzhou-Foshan-Shenzhen (GFS region), and emissions from Guangzhou (local)——were investigated using the Weather Research and Forecasting-Community Multiscale Air Quality model. The results showed that the source region contribution differed with different weather systems. SP was a stagnant weather condition, and the source region contribution ratio showed that the local region was a major contributor (37%), while the PRD region, GFS region and the super-region only contributed 8%, 2.8% and 7%, respectively, to PM2.5 concentrations. By contrast, FC favored regional transport. The super-region became noticeable, contributing 34.8%, while the local region decreased to 12%. A simple method was proposed to quantify the relative impact of meteorology and emissions. Meteorology had a 35% impact, compared with an impact of -18% for emissions, when comparing the FC-affected event with that of the SP. The results from this study can provide guidance to policymakers for the implementation of effective control strategies.