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Lixin Qu, Leif N. Thomas, and Robert D. Hetland

Abstract

This study describes a specific type of critical layer for near-inertial waves (NIWs) that forms when isopycnals run parallel to sloping bathymetry. Upon entering this slantwise critical layer, the group velocity of the waves decreases to zero and the NIWs become trapped and amplified, which can enhance mixing. A realistic simulation of anticyclonic eddies on the Texas–Louisiana shelf reveals that such critical layers can form where the eddies impinge onto the sloping bottom. Velocity shear bands in the simulation indicate that wind-forced NIWs are radiated downward from the surface in the eddies, bend upward near the bottom, and enter critical layers over the continental shelf, resulting in inertially modulated enhanced mixing. Idealized simulations designed to capture this flow reproduce the wave propagation and enhanced mixing. The link between the enhanced mixing and wave trapping in the slantwise critical layer is made using ray tracing and an analysis of the waves’ energetics in the idealized simulations. An ensemble of simulations is performed spanning the relevant parameter space that demonstrates that the strength of the mixing is correlated with the degree to which NIWs are trapped in the critical layers. While the application here is for a shallow coastal setting, the mechanisms could be active in the open ocean as well where isopycnals align with bathymetry.

Open access
Xu Zhang, Yuhua Yang, Baode Chen, and Wei Huang

Abstract

The quantitative precipitation forecast in the 9-km operational modeling system (without the use of a convection parameterization scheme) at the Shanghai Meteorological Service (SMS) usually suffers from excessive precipitation at the grid scale and less-structured precipitation patterns. Two scale-aware convection parameterizations were tested in the operational system to mitigate these deficiencies. Their impacts on the warm-season precipitation forecast over China were analyzed in case studies and two-month retrospective forecasts. The results from case studies show that the importance of convection parameterization depends on geographical regions and weather regimes. Considering a proper magnitude of parameterized convection can produce more realistic precipitation distribution and reduce excessive gridscale precipitation in southern China. In northeast and southwest China, however, the convection parameterization plays an insignificant role in precipitation forecast because of strong synoptic-scale forcing. A statistical evaluation of the two-month retrospective forecasts indicates that the forecast skill for precipitation in the 9-km operational system is improved by choosing proper convection parameterization. This study suggests that improvement in contemporary convection parameterizations is needed for their usage for various meteorological conditions and reasonable partitioning between parameterized and resolved convection.

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Evan A. Kalina, Isidora Jankov, Trevor Alcott, Joseph Olson, Jeffrey Beck, Judith Berner, David Dowell, and Curtis Alexander

Abstract

The High-Resolution Rapid Refresh Ensemble (HRRRE) is a 36-member ensemble analysis system with 9 forecast members that utilizes the Advanced Research version of the Weather Research and Forecasting (ARW-WRF) dynamic core and the physics suite from the operational Rapid Refresh/High-Resolution Rapid Refresh deterministic modeling system. A goal of HRRRE development is a system with sufficient spread among members, comparable in magnitude to the random error in the ensemble mean, to represent the range of possible future atmospheric states. HRRRE member diversity has traditionally been obtained by perturbing the initial and lateral boundary conditions of each member, but recent development has focused on implementing stochastic approaches in HRRRE to generate additional spread. These techniques were tested in retrospective experiments and in the May 2019 Hazardous Weather Testbed Spring Experiment (HWT-SE). Results show a 6%–25% increase in the ensemble spread in 2-m temperature, 2-m mixing ratio, and 10-m wind speed when stochastic parameter perturbations are used in HRRRE (HRRRE-SPP). Case studies from HWT-SE demonstrate that HRRRE-SPP performed similar to or better than the operational High-Resolution Ensemble Forecast system, version 2 (HREFv2), and the nonstochastic HRRRE. However, subjective evaluations provided by HWT-SE forecasters indicated that overall, HRRRE-SPP predicted lower probabilities of severe weather (using updraft helicity as a proxy) compared to HREFv2. A statistical analysis of the performance of HRRRE-SPP and HREFv2 from the 2019 summer convective season supports this claim, but also demonstrates that the two systems have similar reliability for prediction of severe weather using updraft helicity.

Open access
John R. Mecikalski, Thea N. Sandmæl, Elisa M. Murillo, Cameron R. Homeyer, Kristopher M. Bedka, Jason M. Apke, and Chris P. Jewett

Abstract

Few studies have assessed combined satellite, lightning, and radar databases to diagnose severe storm potential. The research goal here is to evaluate next-generation, 60-s update frequency geostationary satellite and lightning information with ground-based radar to isolate which variables, when used in concert, provide skillful discriminatory information for identifying severe (hail ≥ 2.5 cm in diameter, winds ≥ 25 m s−1, and tornadoes) versus nonsevere storms. The focus of this study is predicting severe thunderstorm and tornado warnings. A total of 2004 storms in 2014–15 were objectively tracked with 49 potential predictor fields related to May, daytime Great Plains convective storms. All storms occurred when 1-min Geostationary Operational Environmental Satellite (GOES)-14 “super rapid scan” data were available. The study used three importance methods to assess predictor importance related to severe warnings and used random forests to provide a model and skill evaluation measuring the ability to predict severe storms. Three predictor importance methods show that GOES mesoscale atmospheric-motion-vector-derived cloud-top divergence and above-anvil cirrus plume presence provide the most satellite-based discriminatory power for diagnosing severe warnings. Other important fields include Earth Networks Total Lightning flash density, GOES estimated cloud-top vorticity, and overshooting-top presence. Severe warning predictions are significantly improved at the 95% confidence level when a few important satellite and lightning fields are combined with radar fields, versus when only radar data are used in the random-forest model. This study provides a basis for including satellite and lightning fields within machine-learning models to help forecast severe weather.

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Yoshi N. Sasaki and Chisato Umeda

Abstract

It has been reported that the sea surface temperature (SST) trend of the East China Sea during the twentieth century was a couple of times larger than the global mean SST trend. However, the detailed spatial structure of the SST trend in the East China Sea and its mechanism have not been understood. The present study examines the SST trend in the East China Sea from 1901 to 2010 using observational data and a Regional Ocean Modeling System (ROMS) with an eddy-resolving horizontal resolution. A comparison among two observational datasets and the model output reveals that enhanced SST warming occurred along the Kuroshio and along the coast of China over the continental shelf. In both regions, the SST trends were the largest in winter. The heat budget analysis using the model output indicates that the upper-layer temperature rises in both regions were induced by the trend of ocean advection, which was balanced in relation to the increase of surface net heat release. In addition, the rapid SST warming along the Kuroshio was induced by the acceleration of the Kuroshio. Sensitivity experiments revealed that this acceleration was likely caused by the negative wind stress curl anomalies over the North Pacific. In contrast, the enhanced SST warming along the China coast resulted from the ocean circulation change over the continental shelf by local atmospheric forcing.

Open access
Valerio Capecchi

Abstract

We investigate the potential added value of running three limited-area ensemble systems (with the WRF, Meso-NH, and MOLOCH models and a grid spacing of approximately 2.5 km) for two heavy-precipitation events in Italy. Such high-resolution ensembles include an explicit treatment of convective processes and dynamically downscale the ECMWF global ensemble predictions, which have a grid spacing of approximately 18 km. The predictions are verified against rain gauge data, and their accuracy is evaluated over that of the driving coarser-resolution ensemble system. Furthermore, we compare the simulation speed (defined as the ratio of simulation length to wall-clock time) of the three limited-area models to estimate the computational effort for operational convection-permitting ensemble forecasting. We also study how the simulation wall-clock time scales with increasing numbers of computing elements (from 36 to 1152 cores). Objective verification methods generally show that convection-permitting forecasts outperform global forecasts for both events, although precipitation peaks remain largely underestimated for one of the two events. Comparing simulation speeds, the MOLOCH model is the fastest and the Meso-NH is the slowest one. The WRF Model attains efficient scalability, whereas it is limited for the Meso-NH and MOLOCH models when using more than 288 cores. We finally demonstrate how the model simulation speed has the largest impact on a joint evaluation with the model performance because the accuracy of the three limited-area ensembles, amplifying the forecasting capability of the global predictions, does not differ substantially.

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Seiji Kato, Norman G. Loeb, John T. Fasullo, Kevin E. Trenberth, Peter H. Lauritzen, Fred G. Rose, David A. Rutan, and Masaki Satoh

Abstract

Effects of water mass imbalance and hydrometeor transport on the enthalpy flux and water phase on diabatic heating rate in computing the regional energy and water budget of the atmosphere over ocean are investigated. Equations of energy and water budget of the atmospheric column that explicitly consider the velocity of liquid and ice cloud particles, and rain and snow are formulated by separating water variables from dry air. Differences of energy budget equations formulated in this study from those used in earlier studies are that 1) diabatic heating rate depends on water phase, 2) diabatic heating due to net condensation of nonprecipitating hydrometeors is included, and 3) hydrometeors can be advected with a different velocity from the dry-air velocity. Convergence of water vapor associated with phase change and horizontal transport of hydrometeors is to increase diabatic heating in the atmospheric column where hydrometeors are formed and exported and to reduce energy where hydrometeors are imported and evaporated. The process can improve the regional energy and water mass balance when energy data products are integrated. Effects of enthalpy transport associated with water mass transport through the surface are cooling to the atmosphere and warming to the ocean when the enthalpy is averaged over the global ocean. There is no net effect to the atmosphere and ocean columns combined. While precipitation phase changes the regional diabatic heating rate up to 15 W m−2, the dependence of the global mean value on the temperature threshold of melting snow to form rain is less than 1 W m−2.

Open access
Chunyong Jung and Gary M. Lackmann

Abstract

This study uses small ensembles of convection-allowing, quasi-idealized simulations to examine the response of North Atlantic tropical cyclones (TCs) undergoing extratropical transition (ET) to climate change. Using HURDAT2 and ERA5 data over a 40-yr period from 1979 to 2018, we developed storm-relative composite fields for past North Atlantic recurving, oceanic ET events. The quasi-idealized present-day simulations are initialized from these composites and run in an aquaplanet domain. A pseudo–global warming approach is used for future simulations: Thermodynamic changes between late twenty-first century and twentieth century, derived from an ensemble of 20 CMIP5 GCMs under the RCP8.5 scenario, are added to the present-day initial and lateral boundary conditions. The composite-initialized present-day simulations exhibit realistic ET characteristics. Future simulations show greater intensity, heavier precipitation, and stronger downstream midlatitude wave train development relative to the present-day case. Specifically, the future ET event is substantially stronger before ET completion, though the system undergoes less reintensification after ET completion. Reductions in lower-tropospheric baroclinicity associated with Arctic amplification could contribute to this result. The future simulation exhibits 3-hourly ensemble-mean precipitation rate increases ranging from ~23% to ~50%, depending on ET phase and averaging radius. In addition, larger eddy kinetic energy accompanies the future storm, partly created by increased baroclinic conversion, resulting in stronger amplification of downstream energy maxima via intensified ageostrophic geopotential flux convergence and divergence. These results suggest that future TCs undergoing ET could have greater potential to cause high-impact weather in western Europe through both direct and remote processes.

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Camille Hankel and Eli Tziperman

Abstract

Winter Arctic sea ice loss has been simulated with varying degrees of abruptness across global climate models (GCMs) run in phase 5 of the Coupled Model Intercomparison Project (CMIP5) under the high-emissions extended RCP8.5 scenario. Previous studies have proposed various mechanisms to explain modeled abrupt winter sea ice loss, such as the existence of a wintertime convective cloud feedback or the role of the freezing point as a natural threshold, but none have sought to explain the variability of the abruptness of winter sea ice loss across GCMs. Here we propose a year-to-year local positive feedback cycle in which warm, open oceans at the start of winter allow for the moistening and warming of the lower atmosphere, which in turn increases the downward clear-sky longwave radiation at the surface and suppresses ocean freezing. This situation leads to delayed and diminished winter sea ice growth and allows for increased shortwave absorption from lowered surface albedo during springtime. Last, the ocean stores this additional heat throughout the summer and autumn seasons, setting up even warmer ocean conditions that lead to further sea ice reduction. We show that the strength of this feedback, as measured by the partial temperature contributions of the different surface heat fluxes, correlates strongly with the abruptness of winter sea ice loss across models. Thus, we suggest that this feedback mechanism may explain intermodel spread in the abruptness of winter sea ice loss. In models in which the feedback mechanism is strong, this may indicate the possibility of hysteresis and thus irreversibility of sea ice loss.

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Guixing Chen, Yu Du, and Zhiping Wen

Abstract

This study revisits the long-term variabilities of the East Asian summer monsoon (EASM) in 1958–2017 through examination of diurnal cycles. We group monsoon days into four dynamic quadrants (Q1 to Q4), with emphasis on the strong daily southerlies coupled with a large (Q1) or small (Q4) diurnal amplitude over Southeast China. The occurrence day of Q1 increases in June–July with the seasonal progress of the EASM. It is most pronounced in the 1960s to the 1970s and declines to the lowest in the 1980s to the 1990s, whereas the Q4 occurrence increases notably from the 1970s to the 1990s; both groups return to normal in recent years. The interdecadal decrease (increase) of Q1 (Q4) occurrence corresponds well to the known weakening of EASM in the twentieth century, and it also coincides with the rainfall anomalies over China shifting from a “north flooding and south drought” to a “north drought and south flooding” mode. The rainfall under Q1 (Q4) can account for ~60% of the interannual variance of summer rainfall in northern (southern) China. The contrasting effects of Q1 and Q4 on rainfall are due to their remarkably different regulation on water vapor transport and convergence. The interannual/interdecadal variations of Q1 (Q4) occurrence determine the anomalous water vapor transports to northern (southern) China, in association with the various expansion of the western Pacific subtropical high. In particular, Q1 conditions can greatly intensify nighttime moisture convergence, which is responsible for the long-term variations of rainfall in northern China. The results highlight that the diurnal cycles in monsoon flow act as a key regional process working with large-scale circulation to regulate the spatial distributions and long-term variabilities of EASM rainfall.

Open access