The heat is on: Observations and trends of heat stress metrics during Florida summers

Extreme heat is annually the deadliest weather hazard in the U.S. and is strongly amplified by climate change. In Florida, summer heat waves have increased in frequency and duration, exacerbating negative human health impacts on a state with a substantial older population and industries (e.g., agriculture) that require frequent outdoor work. However, the combined impacts of temperature and humidity (heat stress) have not been previously investigated. For eight Florida cities, this study constructs summer climatologies and trend analyses (1950–2020) of two heat stress metrics: heat index (HI) and wet bulb globe temperature (WBGT). While both incorporate temperature and humidity, WBGT also includes wind and solar radiation, and is a more comprehensive measure of heat stress on the human body. With minor exceptions, results show increases in average summer daily maximum, mean, and minimum HI and WBGT throughout Florida. Daily minimum HI and WBGT exhibit statistically significant increases at all eight stations, emphasizing a hazardous rise in nighttime heat stress. Corresponding to other recent studies, HI and WBGT increases are largest in coastal subtropical locations in Central and South Florida (i.e., Daytona Beach, Tampa, Miami, Key West), but exhibit no conclusive relationship with urbanization changes. Finally, danger (103–124°F) HI and high (> 88°F) WBGT summer days exhibit significant frequency increases across the state. Especially at coastal locations in the Florida Peninsula and Keys, danger HI and high WBGT days now account for > 20% of total summer days, emphasizing a substantial escalation in heat stress, particularly since 2000.

The Application of a Genetic Algorithm to the Optimization of a Mesoscale Model for Emergency Response

Besides solving the equations of momentum, heat, and moisture transport on the model grid, mesoscale weather models must account for subgrid-scale processes that affect the resolved model variables. These are simulated with model parameterizations, which often rely on values preset by the user. Such ‘free’ model parameters, along with others set to initialize the model, are often poorly constrained, requiring that a user select each from a range of plausible values. Finding the values to optimize any forecasting tool can be accomplished with a search algorithm, and one such process – the genetic algorithm (GA) – has become especially popular. As applied to modeling, GAs represent a Darwinian process – an ensemble of simulations is run with a different set of parameter values for each member, and the members subsequently judged to be most accurate are selected as ‘parents’ who pass their parameters onto a new generation. At the Department of Energy’s Savannah River Site in South Carolina, we are applying a GA to the Regional Atmospheric Modeling System (RAMS) mesoscale weather model, which supplies input to a model to simulate the dispersion of an airborne contaminant as part of the site’s emergency response preparations. An ensemble of forecasts is run each day, weather data are used to ‘score’ the individual members of the ensemble, and the parameters from the best members are used for the next day’s forecasts. As meteorological conditions change, the parameters change as well, maintaining a model configuration that is best adapted to atmospheric conditions.

Recent Changes in Average Recurrence Interval Precipitation Extremes in the Middle-Atlantic United States

Increases in the frequency of extreme rainfall occurrence have emerged as one of the more consistent climate trends in recent decades, particularly in the eastern United States. Such changes challenge the veracity of the conventional assumption of stationarity that has been applied in the published extreme rainfall analyses that are the foundation for engineering design assessments and resiliency planning. Using partial duration series with varying record lengths, temporal changes in daily and hourly rainfall extremes corresponding to average annual recurrence probabilities ranging from 50% (i.e. the 2-year storm) to 1% (i.e. the 100-year storm) are evaluated. From 2000 through 2019, extreme rainfall amounts across a range of durations and recurrence probabilities have increased at 75% of the long-term precipitation observation stations in the Middle-Atlantic region. At about a quarter of the stations, increases in extreme rainfall have exceeded 5% from 2000 through 2019, with some stations experiencing increases in excess of 10% for both daily and hourly durations. At over 40% of the stations the rainfall extremes based on the 1950-1999 partial duration series show a significant (p >0.90) change in the 100-yr ARI relative to the 1950-2019 period. Collectively the results indicate that given recent trends in extreme rainfall, routine updates of extreme rainfall analyses are warranted on 20-year intervals.

Climatology of aerosols over the Caribbean islands: aerosol types, synoptic patterns and transport

We present a climatological study of aerosols in four representative Caribbean islands based on daily mean values of aerosol optical properties for the period 2008- 2016, using the Aerosol Optical Depth (AOD) and Ångström Exponent (AE) to classify the dominant aerosol type. A climatological assessment of the spatio-temporal distribution of the main aerosol types, their links with synoptic patterns and the transport from different sources is provided. Maximum values of AOD occur in the rainy season, coinciding with the minimum in AE and an increased occurrence of dust, while the minimum of AOD occurs in the dry season, due to the predominance of marine aerosols. Marine and dust aerosol are more frequent in the easternmost islands and decrease westwards due to an increasing of continental and mixture dust aerosols. Therefore, the westernmost station displays the most heterogeneous composition of aerosols. Using a weather type classification, we identify a quantifiable influence of the atmospheric circulation in the distribution of Caribbean aerosols. However, they can occur under relatively weak and/or diverse synoptic patterns, typically involving transient systems and specific configurations of the Azores High that depend on the considered station. Backward trajectories indicate that dry-season marine aerosols and rainy-season dust are transported by air parcels travelling within the tropical easterly winds. The main source region for both types of aerosols is the subtropical eastern Atlantic, except for Cuba, where the largest contributor to dry-season marine aerosols is the subtropical western Atlantic. Different aerosol types follow similar pathways, suggesting a key role of emission sources in determining the spatio-temporal distribution of Caribbean aerosols.

Comprehensive assessment and variation characteristics of the drought intensity in North China based on EID

Under the new background of climate change, it is very important to identify the characteristics of drought in North China. Based on the daily Meteorological Drought Comprehensive Index from 494 national meteorological stations in North China during 1961–2019, the drought processes and their intensity are identified by applying the ‘extreme’ intensity-duration theory. Then, the stage variation characteristics of the drought trend, the average drought intensity and the drought frequency are analyzed. The results show that among the five drought intensity indexes the process maximum intensity demonstrates the greatest correlation coefficient with the disaster rate of drought in North China. Therefore, the process maximum intensity of drought is selected as the annual drought intensity to analyze the drought characteristics in North China. According to the climate warming trends, the study period is divided into three stages, i.e., 1951–1984 (stage I), 1985–1997 (stage II) and 1998–2019(stage III). The comprehensive results show that the drought intensity in North China has significant stage characteristics. In stage I, the drought shows an increasing trend in most parts of North China, but its average intensity is relatively weaker, with a lower severe drought frequency. The drought also shows an increasing trend in most parts in stage II, with a more significant increase rate than that in stage I, and the average drought intensity is the strongest and the severe drought frequency is the highest. In stage III, the drought shows a decreasing trend in some areas, and the average intensity is the weakest, with a lower severe drought frequency.

Spatio-temporal modeling of the wind field over an urban lake subject to wind sheltering

The wind field over an urban lake may exhibit considerable variability due to wind shielding effects from surrounding structures. Field measurements at an urban reservoir in Singapore were augmented by computational fluid dynamics (CFD) model results to develop a wind model over the reservoir surface via a data assimilation approach. The field measurements identified, depending on structure alignment with the prevailing wind direction, wind shielding that impacted wind direction and velocity over the reservoir surface. The wind model integrated the temporal response of the measurements and spatial distribution produced by the CFD modelling. The wind model was used to predict the spatio-temporal pattern of the wind field over the reservoir surface for a full year. The modeling results showed good agreement with measured wind data at three measurement locations on the reservoir surface. The wind model has been incorporated with a hydrodynamics and water quality model to provide the spatio-temporal wind forcing over the reservoir surface.

A Hybrid Bulk Algorithm to Predict Turbulent Fluxes over Dry and Wet Bare Soils

Measurements made in the Columbia River Basin (Oregon) in an area of irregular terrain during the second Wind Forecast Improvement Project (WFIP 2) field campaign are used to develop an optimized hybrid bulk algorithm to predict the surface turbulent fluxes from readily measured or modelled quantities over dry and wet bare or lightly vegetated soil surfaces. The hybrid (synthetic) algorithm combines (i) an aerodynamic method for turbulent flow which is based on the transfer coefficients (drag coefficient and Stanton number), roughness lengths, and Monin-Obukhov similarity and (ii) a modified Priestley-Taylor (P-T) algorithm with physically based ecophysiological constraints which is essentially based on the surface energy budget (SEB) equation. Soil heat flux in the latter case was estimated from measurements of soil temperature and soil moisture. In the framework of the hybrid algorithm, bulk estimates of the momentum flux and the sensible heat flux are derived from a traditional aerodynamic approach, whereas the latent heat flux (or moisture flux) is evaluated from a modified P-T model. Direct measurements of the surface fluxes (turbulent and radiative) and other ancillary atmospheric/soil parameters made during WFIP 2 for different soil conditions (dry and wet) are used to optimize and tune the hybrid bulk algorithm. The bulk flux estimates are validated against the measured eddy-covariance fluxes. We also discuss the SEB closure over dry and wet surfaces at various timescales based on the modelled and measured fluxes. Although this bulk flux algorithm is optimized for the data collected during the WFIP 2, a hybrid approach can be used for similar flux-tower sites and field campaigns.

Observed and Modeled Urban Heat Island and Sea Breeze Circulation Interactions: a Shanghai Case Study

Urban heat island (UHI) and sea-land breeze systems are well-known and important characteristics of the climate of coastal cities. To model these, the accurate estimation of the surface energy balance (SEB) is a key factor needed to improve local scale simulations of thermodynamic and dynamic boundary circulations. The Weather Research and Forecasting model with a single layer urban model (WRF/SLUCM), with parameters derived from MODIS and local GIS information, is used to investigate the UHI and sea breeze circulations (SBC) in the megacity of Shanghai. The WRF/SLUCM can reproduce observed urban radiation and SEB fluxes, near-surface meteorological variables, and the evolution of the UHI and SBC. Simulations for an August period show the maximum UHI tends to drift northwest in the afternoon, driven by the prevailing southeast wind. The sea breeze lasts for about 4-h and is strongest between 1200 and 1400 Local Time (UTC+8 h). The interaction between UHI and SBC is evident with low-level convergence, upward motion and moisture transport from the sea and urban breezes simulated. An urban circulation (horizontal/vertical/time scales: ∼20-km/ ∼1.5-km/ ∼3-h) with thermal vertical motions (∼1.5 m s−1) above the urban area and a SBC (horizontal/vertical/time scales: 6 - 7 km/ ∼1 km/ 2 - 3-h) above the northern coastal suburb occur. Combined the sea breeze and southerly winds form a low-level wind shear (convergence zone) ∼5 km from the coast that penetrates ∼20 km inland to the urban center. Using the WRF/SLUCM simulations we improve understanding of the complex spatial dynamics of summer-time urban heating in coastal megacities, such as Shanghai.

Air temperature variability in high-elevation glacierized regions: observations from six catchments on the Tibetan Plateau

Near-surface air temperature variability and the reliability of temperature extrapolation within glacierized regions are important issues for hydrological and glaciological studies that remain elusive because of the scarcity of high-elevation observations. Based on air temperature data in 2019 collected from 12 automatic weather stations, 43 temperature loggers and 6 national meteorological stations in six different catchments, this study presents air temperature variability in different glacierized/nonglacierized regions and assesses the robustness of different temperature extrapolations to reduce errors in melt estimation. The results show high spatial variability in temperature lapse rates (LRs) in different climatic contexts, with the steepest LRs located on the cold-dry northwestern Tibetan Plateau and the lowest LRs located on the warm-humid monsoonal-influenced southeastern Tibetan Plateau. Near-surface air temperatures in high-elevation glacierized regions of the western and central Tibetan Plateau are less influenced by katabatic winds and thus can be linearly extrapolated from off-glacier records. In contrast, the local katabatic winds prevailing on the temperate glaciers of the southeastern Tibetan Plateau exert pronounced cooling effects on the ambient air temperature, and thus, on-glacier air temperatures are significantly lower than that in elevation-equivalent nonglacierized regions. Consequently, linear temperature extrapolation from low-elevation nonglacierized stations may lead to as much as 40% overestimation of positive degree days, particularly with respect to large glaciers with a long flowline distances and significant cooling effects. These findings provide noteworthy evidence that the different LRs and relevant cooling effects on high-elevation glaciers under distinct climatic regimes should be carefully accounted for when estimating glacier melting on the Tibetan Plateau.

Rapid change in surface-based temperature inversions across the world during the last three decades

Surface-based inversions (SBIs) are significant and common natural phenomena in the planetary boundary layer, and they play essential roles in weather and climate. This study used radiosonde data from 493 radiosonde stations worldwide from the Integrated Global Radiosonde Archive (IGRA) during 1989–2019 to investigate the variations in surface-based inversions from a global perspective. The results indicated that from 1989 to 2019, the SBI frequency increased, and the SBI strength variations with fluctuations and SBI depth decreased over the study period. However, the spatial distribution of frequency, strength, and depth did not have consistent trends. Compared with the Southern Hemisphere, SBIs in the Northern Hemisphere occurred more frequently and were stronger and deeper. In terms of stations over land and the ocean, we found that the SBI frequency over the ocean has increased faster than that over land in the past 15 years, and the SBI strength over land was almost twice that of the ocean. The amplitudes of the annual cycle of SBI characteristics over land were greater than over the ocean in both hemispheres, and the frequency, strength, and depth were greater over land. This study investigated surface-based inversions from a global perspective and filled a gap in the current research on SBIs.