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Dominique Bouniol, Rémy Roca, Thomas Fiolleau, and Patrick Raberanto

Abstract

The evolution of radiative properties (outgoing longwave radiation, OLR, and albedo at the top of the atmosphere) over Mesoscale Convective System (MCS) life cycle is assessed using five years of Scanner for Radiation Budget (ScaRaB) radiometer onboard the Megha-Tropiques satellites merged with geostationary infrared images. The MCS life cycle is documented using a tracking algorithm. A composite approach is then implemented to document the evolution of radiative properties at each life stage at the scale of the tropical belt, in continental and oceanic regions and in specific regions. Independently of the considered region the composites share similarities with a unique maximum in albedo and a unique minimum in OLR, values of which differ depending on the environment as well as the amplitude of both parameters over the life cycle. The unique precessing orbit of the Megha-Tropiques satellite allows a consideration of the albedo as a function of the local time of observation showing that the magnitude of the albedo signal is mainly controlled by the solar zenithal angle.

Sensitivity tests allow to the quantification of the impact of an error in radiative properties showing that even small errors lead to substantial increment on the instantaneous cloud radiative effect. All together these elements point toward the subtle balance between life cycle, cloud radiative properties and phasing within the diurnal cycle to build the atmospheric radiative budget in oceanic or continental regions.

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Katja Friedrich, Jeffrey R. French, Sarah A. Tessendorf, Melinda Hatt, Courtney Weeks, Robert M. Rauber, Bart Geerts, Lulin Xue, Roy M. Rasmussen, Derek R. Blestrud, Melvin L. Kunkel, Nicholas Dawson, and Shaun Parkinson

Abstract

The spatial distribution and magnitude of snowfall resulting from cloud seeding with silver iodide (AgI) is closely linked to atmospheric conditions, seeding operations, and dynamical, thermodynamical, and microphysical processes. Here, microphysical processes leading to ice and snow production are analyzed in orographic clouds for three cloud-seeding events, each with light or no natural precipitation and well-defined, traceable seeding lines. Airborne and ground-based radar observations are linked to in situ cloud and precipitation measurements to determine the spatiotemporal evolution of ice initiation, particle growth, and snow fallout in seeded clouds. These processes and surface snow amounts are explored as particle plumes evolve from varying amounts of AgI released, and within changing environmental conditions, including changes in liquid water content (LWC) along and downwind of the seeding track, wind speed, and shear. More AgI did not necessarily produce more liquid equivalent snowfall (LESnow). The greatest amount of LESnow, largest area covered by snowfall, and highest peak snowfall produced through seeding occurred on the day with the largest and most widespread occurrence of supercooled drizzle, highest wind shear, and greater LWC along and downwind of the seeding track. The day with the least supercooled drizzle and the lowest LWC downwind of the seeding track produced the smallest amount of LESnow through seeding. The stronger the wind was, the farther away the snowfall occurred from the seeding track.

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Jacob T. Carlin, Heather D. Reeves, and Alexander V. Ryzhkov

Abstract

Snow sublimating in dry air is a forecasting challenge and can delay the onset of surface snowfall and affect storm-total accumulations. Despite this, it remains comparatively less studied than other microphysical processes. Herein, the characteristics of sublimating snow and the potential for nowcasting snowfall reaching the surface are explored through the use of dual-polarization radar. Twelve cases featuring prolific sublimation were analyzed using range-defined quasi-vertical profiles (RDQVPs) and compared with environmental model analyses. Overall, reflectivity Z significantly decreases, differential reflectivity Z DR slightly decreases, and copolar-correlation coefficient ρhv remains nearly constant through the sublimation layer. Regions of enhanced specific differential phase K dp were frequently observed in the sublimation layer and are believed to be polarimetric evidence of secondary ice production via sublimation. A 1D bin model was initialized using particle size distributions retrieved from the RDQVPs using numerous novel polarimetric snowretrieval relations for a wide range of forecast lead times, with the model environment evolving in response to sublimation. It was found that the model was largely able to predict the snowfall start time up to six hours in advance, with a 6-h median bias of just -18.5 minutes. A more detailed case study of the 08 December 2013 snowstorm in the Philadelphia region was also performed, demonstrating good correspondence with observations and examples of model fields (e.g., cooling rate) hypothetically available from such a tool. The proof-of-concept results herein demonstrate the potential benefits of incorporating spatially averaged radar data in conjunction with simple 1D models into the nowcasting process.

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G. Duan and T. Takemi

Abstract

The surface roughness aerodynamic parameters z 0 (roughness length) and d (zero-plane displacement height) are vital to the accuracy of the Monin–Obukhov similarity theory. Deriving improved urban canopy parameterization (UCP) schemes within the conventional framework remains mathematically challenging. The current study explores the potential of a machine-learning (ML) algorithm, a random forest (RF), as a complement to the traditional UCP schemes. Using large-eddy simulation and ensemble sampling, in combination with nonlinear least squares regression of the logarithmic-layer wind profiles, a dataset of approximately 4.5 × 103 samples is established for the aerodynamic parameters and the morphometric statistics, enabling the training of the ML model. While the prediction for d is not as good as the UCP after Kanda et al., the performance for z 0 is notable. The RF algorithm also categorizes z 0 and d with an exceptional performance score: the overall bell-shaped distributions are well predicted, and the ±0.5σ category (i.e., the 38% percentile) is competently captured (37.8% for z 0 and 36.5% for d). Among the morphometric features, the mean and maximum building heights (H ave and H max, respectively) are found to be of predominant influence on the prediction of z 0 and d. A perhaps counterintuitive result is the considerably less striking importance of the building-height variability. Possible reasons are discussed. The feature importance scores could be useful for identifying the contributing factors to the surface aerodynamic characteristics. The results may shed some light on the development of ML-based UCP for mesoscale modeling.

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Zexia Duan, C. S. B. Grimmond, Chloe Y. Gao, Ting Sun, Changwei Liu, Linlin Wang, Yubin Li, and Zhiqiu Gao

Abstract

Quantitative knowledge of the water and energy exchanges in agroecosystems is vital for irrigation management and modeling crop production. In this study, the seasonal and annual variabilities of evapotranspiration (ET) and energy exchanges were investigated under two different crop environments—flooded and aerobic soil conditions—using three years (June 2014–May 2017) of eddy covariance observations over a rice–wheat rotation in eastern China. Across the whole rice–wheat rotation, the average daily ET rates in the rice paddies and wheat fields were 3.6 and 2.4 mm day−1, respectively. The respective average seasonal ET rates were 473 and 387 mm for rice and wheat fields, indicating a higher water consumption for rice than for wheat. Averaging for the three cropping seasons, rice paddies had 52% more latent heat flux than wheat fields, whereas wheat had 73% more sensible heat flux than rice paddies. This resulted in a lower Bowen ratio in the rice paddies (0.14) than in the wheat fields (0.4). Because eddy covariance observations of turbulent heat fluxes are typically less than the available energy (R n − G; i.e., net radiation minus soil heat flux), energy balance closure (EBC) therefore does not occur. For rice, EBC was greatest at the vegetative growth stages (mean: 0.90) after considering the water heat storage, whereas wheat had its best EBC at the ripening stages (mean: 0.86).

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Jeremy E. Diem, Jonathan D. Salerno, Michael W. Palace, Karen Bailey, and Joel Hartter

Abstract

Substantial research on the teleconnections between rainfall and sea surface temperatures (SSTs) has been conducted across equatorial Africa as a whole, but currently no focused examination exists for western Uganda, a rainfall transition zone between eastern equatorial Africa (EEA) and central equatorial Africa (CEA). This study examines correlations between satellite-based rainfall totals in western Uganda and SSTs—and associated indices—across the tropics over 1983–2019. It is found that rainfall throughout western Uganda is teleconnected to SSTs in all tropical oceans but is connected much more strongly to SSTs in the Indian and Pacific Oceans than in the Atlantic Ocean. Increased Indian Ocean SSTs during boreal winter, spring, and autumn and a pattern similar to a positive Indian Ocean dipole during boreal summer are associated with increased rainfall in western Uganda. The most spatially complex teleconnections in western Uganda occur during September–December, with northwestern Uganda being similar to EEA during this period and southwestern Uganda being similar to CEA. During boreal autumn and winter, northwestern Uganda has increased rainfall associated with SST patterns resembling a positive Indian Ocean dipole or El Niño. Southwestern Uganda does not have those teleconnections; in fact, increased rainfall there tends to be more associated with La Niña–like SST patterns. Tropical Atlantic Ocean SSTs also appear to influence rainfall in southwestern Uganda in boreal winter as well as in boreal summer. Overall, western Uganda is a heterogeneous region with respect to rainfall–SST teleconnections; therefore, southwestern Uganda and northwestern Uganda require separate analyses and forecasts, especially during boreal autumn and winter.

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Natalia Odnoletkova and Tadeusz W. Patzek

Abstract

We have analyzed the long-term temperature trends and extreme temperature events in Saudi Arabia between 1979 and 2019. Our study relies on the high resolution, consistent and complete ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). We evaluated linear trends in several climate descriptors, including temperature, dewpoint temperature, thermal comfort and extreme event indices. Previous works on this topic used data from weather station observations over limited time intervals and did not include temperature data for recent years. The years 2010-2019 have been the warmest decade ever observed by instrumental temperature monitoring and comprise the eight warmest years on record. Therefore the earlier results may be incomplete and their results no longer relevant. Our findings indicate that over the past four decades, Saudi Arabia has warmed up at a rate that is 50% higher than the rest of land mass in the Northern Hemisphere. Moreover, moisture content of the air has significantly increased in the region. The increases of temperature and humidity have resulted in the soaring of dew point temperature and thermal discomfort across the country. These increases are more substantial during summers, which are already very hot compared to winters. Such changes may be dangerous to people over vast areas of the country. If the current trend persists into the future, human survival in the region will be impossible without continuous access to air conditioning.

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Timothy Marchok

Abstract

Multiple configurations of the Geophysical Fluid Dynamics Laboratory vortex tracker are tested to determine a setup that produces the best representation of a model forecast tropical cyclone center fix for the purpose of providing track guidance with the highest degree of accuracy and availability. Details of the tracking algorithms are provided, including descriptions of both the Barnes analysis used for center-fixing most variables and a separate scheme used for center-fixing wind circulation. The tracker is tested by running multiple configurations on all storms from the 2015-2017 hurricane seasons in the Atlantic and eastern Pacific Basins using forecasts from two operational National Weather Service models, the Global Forecast System (GFS) and the Hurricane Weather Research and Forecast (HWRF) model. A configuration that tracks only 850 mb geopotential height has the smallest forecast track errors of any configuration based on an individual parameter. However, a configuration composed of the mean of eleven parameters outperforms any of the configurations that are based on individual parameters. Configurations composed of subsets of the eleven parameters and including both mass and momentum variables provide results comparable to or better than the full 11-parameter configuration. In particular, a subset configuration with thickness variables excluded generally outperforms the 11-parameter mean, while one composed of variables from only the 850 mb and near-surface layers performs nearly as well as the 11-parameter mean. Tracker configurations composed of multiple variables are more reliable in providing guidance through the end of a forecast period than are tracker configurations based on individual parameters.

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Jeremy E. Diem, Jonathan D. Salerno, Michael W. Palace, Karen Bailey, and Joel Hartter

Abstract

Substantial research on the teleconnections between rainfall and sea-surface temperatures (SSTs) has been conducted across equatorial Africa as a whole, but currently no focused examination exists for western Uganda, a rainfall transition zone between eastern equatorial Africa (EEA) and central equatorial Africa (CEA). This study examines correlations between satellite-based rainfall totals in western Uganda and SSTs – and associated indices – across the tropics over 1983-2019. It is found that rainfall throughout western Uganda is teleconnected to SSTs in all tropical oceans, but much more strongly to SSTs in the Indian and Pacific Oceans than the Atlantic Ocean. Increased Indian Ocean SSTs during boreal winter, spring, and autumn and a pattern similar to a positive Indian Ocean Dipole during boreal summer are associated with increased rainfall in western Uganda. The most spatially complex teleconnections in western Uganda occur during September-December, with northwestern Uganda being similar to EEA during this period and southwestern Uganda being similar to CEA. During boreal autumn and winter, northwestern Uganda has increased rainfall associated with SST patterns resembling a positive Indian Ocean Dipole or El Niño. Southwestern Uganda does not have those teleconnections; in fact, increased rainfall there tends to be more associated with La Niña-like SST patterns. Tropical Atlantic Ocean SSTs also appear to influence rainfall in southwestern Uganda in boreal winter as well as in boreal summer. Overall, western Uganda is a heterogeneous region with respect to rainfall-SST teleconnections; therefore, southwestern Uganda and northwestern Uganda require separate analyses and forecasts, especially during boreal autumn and winter.

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