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Basivi Radhakrishna and Thota Narayana Rao

Abstract

The diurnal cycle of rainfall by large-scale systems (LSS) and small-scale systems (SSS) has been studied over a complex terrain region (Gadanki) in southern peninsular India using eight years of data from a network of 36 rain gauges. The diurnal cycle of accumulated rainfall by LSS and SSS shows peaks at 2200 and 1900 LT, respectively, during the southwest monsoon (SWM) and at 1900 and ~1700 LT during the northeast monsoon (NEM). Irrespective of the season and system size, the diurnal mode is the dominant mode of variation; it explains ~60% of variance during the SWM and ~54% during the NEM in LSS presence and explains ~43% of variance during the SWM and ~36% during the NEM in SSS presence. The correlation structure of rainfall is anisotropic with an axis ratio of ~1.5 for LSS and ~1.4 for SSS. Propagating systems are prevalent (80%–90% of times produce rain) in the presence of LSS during both seasons and play a dominant role in altering the diurnal cycle of rainfall over the Gadanki region. The conducive environment, like the presence of large relative humidity, updrafts in the lower and midtroposphere, and large lower and small midtropospheric shears, favors convective initiation and propagation of precipitating systems during LSS in SWM and NEM. The atmosphere favors convective initiation between 1800 and 2000 LT. The dry midtroposphere and weak upward motion in the midtroposphere inhibit mesoscale organization and form SSS during the SWM. During the NEM, a somewhat drier midtroposphere than in LSS and small wind shear in the lower troposphere (“L-shear”) inhibit the convective organization and form SSS between 1500 and 1800 LT.

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Jinxin Wang and Xiao-Ming Hu

Abstract

This study evaluated the Weather Research and Forecasting (WRF) Model sensitivity to different planetary boundary layer (PBL) schemes (the YSU and MYJ schemes) and urban schemes including the bulk scheme (BULK), single-layer urban canopy model (UCM), multilayer building environment parameterization (BEP) model, and multilayer building energy model (BEM). Daily reinitialization simulations were conducted over Dallas–Fort Worth during a dry summer month (July 2011) and a wet summer month (July 2015) with weaker (stronger) daytime (nocturnal) UHI in 2011 than 2015. All urban schemes overestimated the urban daytime 2-m temperature in both summers, but BEP and BEM still reproduced the daytime urban cool island in the dry summer. All urban schemes reproduced the nocturnal urban heat island, with BEP producing the weakest one due to its unrealistic urban cooling. BULK and UCM overestimated the urban canopy wind speed, while BEP and BEM underestimated it. The urban schemes showed prominent impact on daytime PBL profiles. UCM + MYJ showed a superior performance than other configurations. The relatively large (small) aspect ratio between building height and road width in UCM (BEM) was responsible for the overprediction (underprediction) of urban canopy temperature. The relatively low (high) building height in UCM (BEM) was responsible for the overprediction (underprediction) of urban canopy wind speed. Improving urban schemes and providing realistic urban parameters were critical for improving urban canopy simulation.

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Brittany N. Carson-Marquis, Jianglong Zhang, Peng Xian, Jeffrey S. Reid, and Jared W. Marquis

Abstract

When unaccounted for in numerical weather prediction (NWP) models, heavy aerosol events can cause significant unrealized biases in forecast meteorological parameters such as surface temperature. To improve near-surface forecasting accuracies during heavy aerosol loadings, we demonstrate the feasibility of incorporating aerosol fields from a global chemical transport model as initial and boundary conditions into a higher-resolution NWP model with aerosol–meteorological coupling. This concept is tested for a major biomass burning smoke event over the northern Great Plains region of the United States that occurred during summer of 2015. Aerosol analyses from the global Navy Aerosol Analysis and Prediction System (NAAPS) are used as initial and boundary conditions for Weather Research and Forecasting Model with Chemistry (WRF-Chem) simulations. Through incorporating more realistic aerosol direct effects into the WRF-Chem simulations, errors in WRF-Chem simulated surface downward shortwave radiative fluxes and near-surface temperature are reduced when compared with surface-based observations. This study confirms the ability to decrease biases induced by the aerosol direct effect for regional NWP forecasts during high-impact aerosol episodes through the incorporation of analyses and forecasts from a global aerosol transport model.

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Christopher P. Loughner, Benjamin Fasoli, Ariel F. Stein, and John C. Lin

Abstract

The Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) is a state-of-the-science atmospheric dispersion model that is developed and maintained at the National Oceanic Atmospheric Administration’s Air Resources Laboratory. In the early 2000s, HYSPLIT served as the starting point for development of the Stochastic Time-Inverted Lagrangian Transport (STILT) model that emphasizes backward-in-time dispersion simulations to determine source regions of receptors. STILT continued its separate development and gained a wide user base. Since STILT was built on a now outdated version of HYSPLIT and lacks long-term institutional support to maintain the model, incorporating STILT features into HYSPLIT allows these features to stay up to date. This paper describes the STILT features incorporated into HYSPLIT, which include a new vertical interpolation algorithm for WRF-derived meteorological input files, a detailed algorithm for estimating boundary layer height, a new turbulence parameterization, a vertical Lagrangian time scale that varies in time and space, a complex dispersion algorithm, and two new convection schemes. An evaluation of these new features was performed using tracer release data from the Cross Appalachian Tracer Experiment and the Across North America Tracer Experiment. Results show that the dispersion module from STILT, which takes up to double the amount of time to run, is less dispersive in the vertical direction and is in better agreement with observations when compared with the existing HYSPLIT option. The other new modeling features from STILT were not consistently statistically different than existing HYSPLIT options. Forward-time simulations from the new model were also compared with backward-in-time equivalents and were found to be statistically comparable to one another.

Open access
Lijuan Wang, Hongchao Zuo, and Wei Wang

Abstract

Fengyun-4A (FY-4A) is a geostationary meteorological satellite with four advanced payloads, which can be used to quantitatively detect Earth’s atmospheric system with multispectral and high spatial and temporal resolution. However, the applicable model limits the application of the FY-4A satellite data. In this paper, the empirical statistical model developed for the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor is extended for FY-4A Advanced Geosynchronous Radiation Imager (AGRI), and it is applied to observed data to evaluate the applicability of the model for AGRI measurements. To improve the accuracy of radiation estimation, the artificially intelligent particle swarm optimization (PSO) algorithm was used for model optimizing. Results show that the estimated radiation has diurnal variation that is in accord with the characteristics of radiation variation. The estimated net surface shortwave radiation (Sn) and observed values show good correlation. However, large deviations from observations are found in the estimated values when the empirical model based on MODIS is directly used to process AGRI data. Thus, the empirical statistical model based on MODIS can be applied to AGRI data, but the empirical parameters need to be revised. Optimization of the empirical statistical model by the PSO algorithm can effectively improve the accuracy of the radiation estimate. The mean absolute percentage error (MAPE) of Sn estimated by optimized models is reduced to 15%. The MAPE of the net surface longwave radiation (Ln) estimated by optimized models is reduced to 31%, and the MAPE of the net radiation (Rn) estimated by optimized models is reduced to 27%. However, for the uncertainty caused by error accumulation effect, the influence of PSO optimization on Rn is not as obvious as that of Ln. However, the analysis of error distribution shows that PSO optimization does improve the estimation results of Rn. Based on AGRI data, the surface radiation can be estimated simply, and the regional or larger-scale surface radiation retrieval can quickly be realized by this method, which has large application potential and popularization value.

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Yi-Jie Zhu, Jennifer M. Collins, and Philip J. Klotzbach

Abstract

Understanding tropical cyclone wind speed decay during the postlandfall stage is critical for inland hazard preparation. This paper examines the spatial variation of wind speed decay of tropical cyclones over the continental United States. We find that tropical cyclones making landfall over the Gulf Coast decay faster within the first 24 h after landfall than those making landfall over the Atlantic East Coast. The variation of the decay rate over the Gulf Coast remains larger than that over the Atlantic East Coast for tropical cyclones that had made landfall more than 24 h prior. Besides an average weaker tropical cyclone landfall intensity, the near-parallel trajectory and the proximity of storms to the coastline also help to explain the slower postlandfall wind speed decay for Atlantic East Coast landfalling tropical cyclones. Tropical cyclones crossing the Florida Peninsula only slowly weaken after landfall, with an average of less than 20% postlandfall wind speed drop while transiting the state. The existence of these spatial variations also brings into question the utility of a uniform wind decay model. While weak intensity decay over the Florida Peninsula is well estimated by the uniform wind decay model, the error from the uniform wind decay model increases with tropical cyclones making direct landfall more parallel to the Atlantic East Coast. The underestimation of inland wind speed by the uniform wind decay model found over the western Gulf Coast brings attention to the role of land–air interactions in the decay of inland tropical cyclones.

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Paul Flanagan and Rezaul Mahmood

Abstract

Extreme precipitation events are challenging to local and regional stakeholders across the United States. The Missouri River basin (MoRB), covering an area over 1.29 million km2, is prone to extreme precipitation events. These events are exacerbated by the complex terrain in the west and the numerous weather and climate features that impact the region on a seasonal and annual basis (low-level jets, mesoscale convective systems, extreme cold air intrusions, etc.). Without an in-depth analysis of extreme precipitation in the MoRB, the evolving nature of extreme precipitation is not known. This situation warrants an analysis of extreme precipitation, especially relating to subannual variations when extreme precipitation is more impactful. To this end, data from 131 U.S. Historical Climatology Network (USHCN) stations were used to determine the nature of extreme precipitation from 1950 to 2019. Annual 99th-percentile events and annual station maximum precipitation events occur more frequently in the eastern MoRB than in the western MoRB, in line with the annual precipitation climatology. Results show that 99th-percentile events and annual station maximum precipitation events are becoming more frequent across the MoRB. Through analysis of 3-month extreme precipitation trends, areas in the eastern and southern MoRB are shown to have an increase in event frequency and intensity. Frequency shifts in the 99th-percentile events, however, have occurred across the entire region. The increasing frequency of extreme events in the western MoRB represents a significant change for the hydroclimate of the region. Overall, the results from this work show that MORB extreme precipitation has increased in frequency and intensity during the 1950–2019 period.

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Carolyne B. Machado, Thamiris L. O. B. Campos, Sameh A. Abou Rafee, Jorge A. Martins, Alice M. Grimm, and Edmilson D. de Freitas

Abstract

In this work, the trend of extreme rainfall indices in the macrometropolis of São Paulo (MMSP) was analyzed and correlated with large-scale climatic oscillations. A cluster analysis divided a set of rain gauge stations into three homogeneous regions within MMSP, according to the annual cycle of rainfall. The entire MMSP presented an increase in the total annual rainfall, from 1940 to 2016, of 3 mm yr−1 on average, according to a Mann–Kendall test. However, there is evidence that the more urbanized areas have a greater increase in the frequency and magnitude of extreme events while coastal and mountainous areas, and regions outside large urban areas, have increasing rainfall in a better-distributed way throughout the year. The evolution of extreme rainfall (95th percentile) is significantly correlated with climatic indices. In the center-north part of the MMSP, the combination of Pacific decadal oscillation (PDO) and Antarctic Oscillation (AAO) explains 45% of the P95th increase during the wet season. In turn, in southern MMSP, the temperature of South Atlantic (TSA), the AAO, El Niño–South Oscillation (ENSO), and the multidecadal oscillation of the North Atlantic (AMO) better explain the increase in extreme rainfall (R 2 = 0.47). However, the same is not observed during the dry season, in which the P95th variation was only negatively correlated with the AMO, undergoing a decrease from the 1970s until the beginning of this century. The occurrence of rainy anomalous months proved to be more frequent and associated with climatic indices than was the occurrence of dry months.

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Christian Philipp Lackner, Bart Geerts, and Yonggang Wang

Abstract

A high-resolution (4 km) regional climate simulation conducted with the Weather Research and Forecasting Model is used to investigate potential impacts of global warming on skiing conditions in the interior western United States (IWUS). Recent-past and near-future climate conditions are compared. The past climate period is from November 1981 to October 2011. The future climate applies to a 30-yr period centered on 2050. A pseudo–global warming approach is used, with the driver reanalysis dataset perturbed by the CMIP5 ensemble mean model guidance. Using the 30-yr retrospective simulation, a vertical adjustment technique is used to determine meteorological parameters in the complex terrain where ski areas are located. For snow water equivalent (SWE), Snowpack Telemetry sites close to ski areas are used to validate the technique and apply a correction to SWE in ski areas. The vulnerability to climate change is assessed for 71 ski areas in the IWUS considering SWE, artificially produced snow, temperature, and rain; 20 of the ski areas will tend to have fewer than 100 days per season with sufficient natural and artificial snow for skiing. These ski areas are located at either low elevations or low latitudes, making these areas the most vulnerable to climate change. Throughout the snow season, natural SWE decreases significantly at the low elevations and low latitudes. At higher elevations, changes in SWE are predicted to not be significant in the midseason. In mid-February, SWE decreases by 11.8% at the top elevations of ski areas and decreases by 25.8% at the base elevations.

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Colin M. Zarzycki, Paul A. Ullrich, and Kevin A. Reed

Abstract

This article describes a software suite that can be used for objective evaluation of tropical cyclones (TCs) in gridded climate data. Using cyclone trajectories derived from 6-hourly data, a comprehensive set of metrics is defined to systematically compare and contrast products with one another. In addition to annual TC climatologies, attention is paid to spatial and temporal patterns of storm occurrence and intensity. Assessment can be performed either on the global scale or for regional domains. Simple-to-visualize “scorecards” allow for rapid credibility assessment. We showcase three key findings enabled by this suite. First, we compare the representation of TCs in seven current-generation global reanalyses and conclude that higher-resolution models and those with TC-specific assimilation contain more accurate storm climatologies. Second, using a free-running Earth system model (ESM) we find that full basin refinement is required in variable-resolution configurations to adequately simulate North Atlantic Ocean TC frequency. Upstream refinement over northern Africa offers little benefit in simulating storm occurrence, but spatial genesis patterns are improved. We also show that TCs simulated by ESMs can be highly sensitive to individual parameterizations in climate models, with North Atlantic TC metrics varying greatly depending on the version of the Morrison–Gettelman microphysics package that is used.

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