precipitation cycle
Recently Published Documents

<p>The Laurentian Great Lakes region has a distinct precipitation seasonality, with highest magnitudes in the summer months of June to September and drier conditions in the winter months (December to March). The region also exhibits a ‘mid-summer drying’ behaviour, where the precipitation magnitude drops from July to August by approximately 7% and recovers in September before declining again in the autumn season. The distinct precipitation seasonal cycle modulates the land hydrological budget and has significance for regional water resources. This study aims to understand the precipitation seasonality in 20 CMIP6 models for historical (1980 – 2014) and mid-century (2030 – 2060) SSP2-4.5 scenario. Seasonal wet/dry biases in historical data are computed using CRU TS4.03 precipitation data as baseline.</p><p>CMIP6 models show a myriad of different patterns, none of which conform to the observed precipitation seasonality. Some models show a singular skewed peak with the maxima in either June or July flowed by slow tapering off until December (e.g., MRI-ESM2.0, CanESM, GFDL-CM4). Various models show a spring and winter-time wet bias (NUIST-NESM3, ACCESS-ESM1-5) and/or underestimation of the summer-season magnitudes (FGOALS-f3-L, NCAR-CESM2, NorESM2-MM). In general, the precipitation seasonality exhibited by the CMIP6 models is not characteristic of the region. We also find that while some models are wet or dry throughout the year, others show only seasonal biases indicating that their convective parameterization and/or microphysics schemes fail to adequality capture precipitation patterns in these seasons. While most CMIP6 models and reanalysis datasets show a gaussian convective precipitation cycle with the annual maxima in July, some models (e.g., BCC-CSM2-MR, NCAR-CESM2) show strong biases in it, indicating issues with their convective schemes.</p><p>These biases and anomalous precipitation cycle can be propagated or even amplified in the future climate model simulations, significantly altering the projections. Therefore, identifying the models that best represent the regional precipitation spatiotemporal characteristics can assist in better assessment of the future changes in the region’s hydroclimate.</p>

Abstract Deficiencies in forecast models commonly stem from inadequate representation of physical processes; yet, improvement to any single physics component within a model may lead to degradations in other physics components or the model as a whole. In this study, a systematic investigation of physics tendencies is demonstrated to help identify and correct compensating sources of model biases. The model improvement process is illustrated by addressing a commonly known issue in warm-season rainfall forecasts from parameterized convection models: the misrepresentation of the diurnal precipitation cycle over land, especially in its timing. Recent advances in closure assumptions in mass-flux cumulus schemes have made remarkable improvements in this respect. Here, we investigate these improvements in the representation of the diurnal precipitation cycle for a spring period over the United States, and how changes to the cumulus scheme impact the model climate and the behavior of other physics schemes. The modified cumulus scheme improves both the timing of the diurnal precipitation cycle and reduces midtropospheric temperature and moisture biases. However, larger temperature and moisture biases are found in the boundary layer as compared to a predecessor scheme, along with an overamplification of the diurnal precipitation cycle, relative to observations. Guided by a tendency analysis, we find that biases in the diurnal amplitude of the precipitation cycle in our simulations, along with temperature and moisture biases in the boundary layer, originate from the land surface model.

Abstract The Maritime Continent is one of the wettest regions on the planet and has been shown to be important for global budgets of heat and moisture. Convection in the region, however, varies on several interrelated scales, making it difficult to quantify the precipitation climate and understand the key processes. For example, the diurnal cycle in precipitation over the land varies substantially according to the phase of the Madden–Julian oscillation (MJO), and the diurnal precipitation cycle over the water is coupled to that over the land, in some cases for distances of over 1000 km from the coast. Here, a 10-yr austral summer climatology of diurnal and MJO-scale variations in rain rate over the land and sea over the Maritime Continent is presented. The climatology is based on mesoscale model simulations with a horizontal grid length of 4 km and satellite precipitation estimates. The amplitude of the observed diurnal precipitation cycle is shown to reach a maximum just prior to the MJO active phase, with a weaker secondary maximum after the MJO active phase. Although these two maxima also exist in the modeled diurnal precipitation cycle, there is less difference between the maxima before and after the MJO active phase than in the observations. The modeled sea-breeze circulation is also shown to possess approximately equal maxima just before and just after the MJO active period, suggesting that the asymmetry of the diurnal precipitation cycle about the MJO active period is related more to moisture availability than kinematic forcing.

Changes in the diurnal precipitation cycle as the Madden–Julian oscillation (MJO) propagates through the Maritime Continent are investigated to explore the processes behind seaward-propagating precipitation northeast of New Guinea. Satellite rainfall estimates from TRMM 3B42 and the Climate Prediction Center morphing technique (CMORPH) are combined with simulations from the Weather Research and Forecasting (WRF) Model with a horizontal resolution of 4 km. Comparison with 24-h rain gauge measurements indicates that both satellite estimates and the WRF Model exhibit systematic biases. Despite these biases, the changing patterns of offshore precipitation with the passage of the MJO show good consistency between satellite estimates and the WRF Model. In the few days prior to the main MJO envelope, light background wind, relatively clear skies, and an increasingly moist environment promote favorable conditions for the diurnal precipitation cycle. Two distinct processes are identified: 100–200 km from the coast, precipitation moves offshore as a squall line with a propagation speed of 3–5 m s−1. Farther offshore, precipitation propagates with a speed close to 18 m s−1and is associated with an inertia–gravity wave generated by diurnally oscillating heating from radiative and moist convective processes over the land. A gravity wave signature is evident even after the MJO active period when there is little precipitation. By correcting for the background flow perpendicular to the coast, potential temperature anomalies for the lead-up, active, and follow-on MJO periods are shown to collapse to a remarkably invariant shape for a given time of day.