Abstract

Because Atlanta, Georgia, is a model of rapid transition from forest/agriculture land use to urbanization, NASA and other agencies have initiated programs to identify and understand how urban heat islands (UHIs) impact the environment in terms of land use, air quality, health, climate, and other factors. Atlanta's UHI may also impact the regional water cycle by inadvertent forcing of precipitating cloud systems. Yet, a focused assessment of the role of urban-induced rainfall in Atlanta has not been a primary focus of past efforts. Several observational and climatological studies have theorized that UHIs can have a significant influence on mesoscale circulations and resulting convection. Using spaceborne rain radar and a limited network of irregularly spaced, ground-based rain gauges, evidence that the Atlanta and Houston, Dallas, and San Antonio, Texas, urban areas may modify cloud and precipitation development was recently found.

To validate these recent satellite-based findings, it was determined that a higher density of rainfall gauges would be required for future work. The NASA-sponsored Study of Precipitation Anomalies from Widespread Urban Landuse (SPRAWL) seeks to further address the impact of urban Atlanta on precipitation variability by implementing a dense rain gauge network to validate spaceborne rainfall estimates. To optimize gauge location to a given set of criteria, a geographical information system (GIS) aided by a spatial decision support system (DSS) has been developed. A multicriteria decision analysis (MCDA) technique was developed to locate optimal sites in accordance to the guidelines defined by the World Meteorological Organization (WMO). A multicriteria analysis model for the optimization of prospective sites was applied to identify prime locations for the tipping-bucket rain gauges. The MCDA design required development of a spatial model by applying a series of linear programming methods, with the aid of spatial analytical techniques, in order to identify land sites that meet a particular set of criteria.

Abstract

The relationship between rainfall characteristics and urbanization over the eastern United States was examined by analyzing four datasets: daily rainfall in 4593 surface stations over the last 50 years (1958–2008), a high-resolution gridded rainfall product, reanalysis wind data, and a proxy for urban land use (gridded human population data). Results indicate that summer monthly rainfall amounts show an increasing trend in urbanized regions. The frequency of heavy rainfall events has a potential positive bias toward urbanized regions. Most notably, consistent with case studies for individual cities, the climatology of rainfall amounts downwind of urban–rural boundaries shows a significant increasing trend. Analysis of heavy (90th percentile) and extreme (99.5th percentile) rainfall events indicated decreasing trends of heavy rainfall events and a possible increasing trend for extreme rainfall event frequency over urban areas. Results indicate that the urbanization impact was more pronounced in the northeastern and midwestern United States with an increase in rainfall amounts. In contrast, the southeastern United States showed a slight decrease in rainfall amounts and heavy rainfall event frequencies. Results suggest that the urbanization signature is becoming detectable in rainfall climatology as an anthropogenic influence affecting regional precipitation; however, extracting this signature is not straightforward and requires eliminating other dynamical confounding feedbacks.

Abstract

A major thunderstorm asthma epidemic struck Melbourne and surrounding Victoria, Australia, on 21 November 2016, which led to multiple deaths, a flood of residents seeking medical attention for respiratory problems, and an overwhelmed emergency management system. This case day had all the classic ingredients for an epidemic, including high rye grass pollen concentrations, a strong multicellular thunderstorm system moving across the region, and a large population of several million people in the vicinity of Melbourne. A particular characteristic of this event was the strong, gusty winds that likely spread the pollen grains and/or allergenic contents widely across the region to increase population exposure. This exploratory case study is the first to examine the usefulness of low-to-middle-atmospheric thermodynamic information for anticipating epidemic thunderstorm asthma outbreaks by allowing the forecast of strong downdraft winds. The authors investigated the utility of several mesoscale products derived from atmospheric soundings such as downdraft convective available potential energy (DCAPE) and indices for predicting surface wind gusts such as microburst wind speed potential index (MWPI) and a wind gust index (GUSTEX). These results indicate that DCAPE levels reached “high” to “very high” thresholds for strong downdraft winds in the lead-up to the thunderstorm, and the MWPI and GUSTEX indices accurately predicted the high maximum surface wind observations. This information may be useful for diagnostic and prognostic assessment of epidemic thunderstorm asthma and in providing an early warning to health practitioners, emergency management officials, and residents in affected areas.

Abstract

Tropical cyclones (TCs) typically weaken or transition to extratropical cyclones after making landfall. However, there are cases of TCs maintaining warm-core structures and intensifying inland unexpectedly, referred to as TC maintenance or intensification events (TCMIs). It has been proposed that wet soils create an atmosphere conducive to TC maintenance by enhancing surface latent heat flux (LHF). In this study, “HYDRUS-1D” is used to simulate the surface energy balance in intensification regions leading up to four different TCMIs. Specifically, the 2-week magnitudes and trends of soil temperature, sensible heat flux (SHF), and LHF are analyzed and compared across regions. While TCMIs are most common over northern Australia, theoretically linked to large fluxes from hot sands, the results revealed that SHF and LHF are equally large over the south-central United States. Modern-Era Retrospective Analysis for Research and Applications (MERRA) 3-hourly LHF data were obtained for the same HYDRUS study regions as well as nearby ocean regions along the TC path 3 days prior (prestorm) to the TC appearance. Results indicate that the simulated prestorm mean LHF is similar in magnitude to that obtained from MERRA, with slightly lower values overall. The modeled 3-day mean fluxes over land are less than those found over the ocean; however, the maximum LHF over the 3-day period is greater over land (HYDRUS) than over the ocean (MERRA) for three of four cases. It is concluded that LHF inland can achieve similar magnitudes to that over the ocean during the daytime and should be pursued as a potential energy source for inland TCs.

Abstract

Flooding is routinely one of the most deadly weather-related hazards in the United States, which highlights the need for more hydrometeorological research related to forecasting these hazardous events. Building upon previous literature, a synergistic study analyzes hydrometeorological aspects of major urban flood events in the United States from 1977 through 2014 caused by locally heavy precipitation. Primary datasets include upper-air soundings and climatological precipitable water (PW) distributions. A major finding of this work is that major urban flood events are associated with extremely anomalous PW values, many of which exceeded the 99th percentile of the associated climatological dataset and all of which were greater than 150% of the climatological mean values. However, of the 40 cases examined in this study, only 15 had PW values that exceeded 50.4 mm (2 in.), illustrating the importance of including the location-specific PW climatology in a PW analysis relevant to the potential for flash floods. Additionally, these events revealed that, despite geographic location and time of year, most had a warm cloud depth of at least 6 km, which is defined here as the layer between the lifting condensation level and the height of the −10°C level. A “composite” flood sounding was also calculated and revealed a characteristically tropical structure, despite cases related to tropical cyclones being excluded from the study.

Abstract

Urban–coastal circulations affect urban weather, dispersion and transport of pollutants and contaminants, and climate. Proper characterization and prediction of thermodynamic and dynamic processes in such environments are warranted. A new generation of observation and modeling systems is enabling unprecedented characterization of the three-dimensionality of the urban environment, including morphological parameters. Urban areas of Houston, Texas, are classified according to lidar-measured building heights and assigned typical urban land surface parameters appropriate to each classification. The lidar data were degraded from 1 m to the model resolution (1 km) with the goal of evaluating the impact of degraded resolution urban canopy parameters (UCPs) and three-dimensionality on the coastal–urban mesoscale circulations in comparison to typical two-dimensional urban slab approaches. The study revealed complex interactions between the sea breeze and urban heat island and offers a novel diagnostic tool, the bulk Richardson shear number, for identifying shallow mesoscale circulation.

Using the Advanced Research Weather Research and Forecasting model (ARW-WRF) coupled to an atmosphere–land surface–urban canopy model, the authors simulated a theoretical sea-breeze day and confirmed that while coastal morphology can itself lead to complex sea-breeze front structures, including preferred areas of vertical motion, the urban environment can have an impact on the evolution of the sea-breeze mesoscale boundary. The inclusion of lidar-derived UCPs, even at degraded resolution, in the model’s land surface representation can lead to significant differences in patterns of skin surface temperature, convergence, and vertical motion, which have implications for many aspects of urban weather.

Abstract

This study uses a database consisting of 330 austral warm-season (October–May) mesoscale convective complexes (MCCs) during 1998–2007 to determine the contribution of MCCs to rainfall across subtropical South America (SSA). A unique precipitation analysis is conducted using Tropical Rainfall Measuring Mission (TRMM) 3B42 version 6 data. The average MCC produces 15.7 mm of rainfall across 381 000 km², with a volume of 7.0 km³. MCCs in SSA have the largest precipitation areas compared to North American and African systems. MCCs accounted for 15%–21% of the total rainfall across portions of northern Argentina and Paraguay during 1998–2007. However, MCCs account for larger fractions of the total precipitation when analyzed on monthly and warm-season time scales. Widespread MCC rainfall contributions of 11%–20% were observed in all months. MCCs accounted for 20%–30% of the total rainfall between November and February, and 30%–50% in December, primarily across northern Argentina and Paraguay. MCCs also produced 25%–66% of the total rainfall across portions of west-central Argentina. Similar MCC rainfall contributions were observed during warm seasons. An MCC impact factor (MIF) was developed to determine the overall impact of MCC rainfall on warm-season precipitation anomalies. Results show that the greatest impacts on precipitation anomalies from MCC rainfall were located near the center of the La Plata basin. This study demonstrates that MCCs in SSA produce widespread precipitation that contributes substantially to the total rainfall across the region.

Abstract

Earlier studies of mesoscale convective system stratiform regions have shown that large electric fields and charge densities are found near the 0°C level. Here 12 soundings of the electric field were analyzed through the 0°C level in various types of electrified stratiform clouds. For each electric field sounding, the thermodynamic sounding and supporting radar data were also studied. For comparison, five soundings not from stratiform clouds were included. Charge densities were found at or near 0°C in the stratiform clouds of at least 1 nC m⁻³ in eight of the soundings, and four of those had charge densities of at least 2 nC m⁻³. Of the stratiform soundings, 11 had an electric field magnitude of greater than 50 kV m⁻¹ near 0°C, and 7 of those had an electric field magnitude of at least 75 kV m⁻¹. The evidence suggests that melting may be the primary cause of the charge density found at and below 0°C in electrified stratiform clouds. In all 12 of the stratiform soundings, positive charge density was found at or near 0°C, and 11 of those had weaker negative charge density below. The evidence further suggests these two features do not exist in the absence of a bright band and (usually) an associated quasi-isothermal layer.

Abstract

An investigation of Tropical Cyclone (TC) Kelvin in February 2018 over northeast Australia was conducted to understand the mechanisms of the brown ocean effect (BOE) and to develop a comprehensive analysis framework for landfalling TCs in the process. NASA’s Land Information System (LIS) coupled to the NASA Unified WRF (NU-WRF) system was employed as the numerical model framework for 12 land/soil moisture perturbation experiments. Impacts of soil moisture and surface enthalpy flux conditions on TC Kelvin were investigated by closely evaluating simulated track and intensity, midlevel atmospheric thermodynamic properties, vertical wind shear, total precipitable water (TPW), and surface moisture flux. The results suggest that there were recognized differentiations among the sensitivity simulations as a result of land surface (e.g., soil moisture and texture) conditions. However, the intensification of TC Kelvin over land was more strongly related to atmospheric moisture advection and the diurnal cycle of solar radiation (i.e., radiative cooling) than to overall soil moisture conditions or surface fluxes. The analysis framework employed here for TC Kelvin can serve as a foundation to specifically quantify the factors governing the BOE. It also demonstrates that the BOE is not a binary influence (i.e., all or nothing), but instead operates in a continuum from largely to minimally influential such that it could be utilized to help improve prediction of inland effects for all landfalling TCs.

Abstract

Extreme heat is the leading weather-related killer in the United States. Vulnerability to extreme heat has previously been identified and mapped in urban areas to improve heat morbidity and mortality prevention efforts. However, only limited work has examined vulnerability outside of urban locations. This study seeks to broaden the geographic context of earlier work and compute heat vulnerability across the state of Georgia, which offers diverse landscapes and populations with varying sociodemographic characteristics. Here, a modified heat vulnerability index (HVI) developed by Reid et al. is used to characterize vulnerability by county. About half of counties with the greatest heat vulnerability index scores contain the larger cities in the state (i.e., Athens, Atlanta, Augusta, Columbus, Macon, and Savannah), while the other half of high-vulnerability counties are located in more rural counties clustered in southwestern and east-central Georgia. The source of vulnerability varied between the more urban and rural high-vulnerability counties, with poverty and population of nonwhite residents driving vulnerability in the more urban counties and social isolation/population of elderly/poor health the dominant factor in the more rural counties. Additionally, the effectiveness of the HVI in identifying vulnerable populations was investigated by examining the effect of modification of the vulnerability index score with mortality during extreme heat. Except for the least vulnerable categories, the relative risk of mortality increases with increasing vulnerability. For the highest-vulnerability counties, oppressively hot days lead to a 7.7% increase in mortality.