Browse
Abstract
This study addresses hurricane hazard to the state of New York in past, present, and future using synthetic storms generated by the Columbia Hazard model (CHAZ) and climate inputs from phase 5 of the Coupled Model Intercomparison Project (CMIP5), in conjunction with historical observations. The projected influence of anthropogenic climate change on future hazard is quantified by the normalized differences in statistics of hurricane hazard between the recent historical period (1951–2005) and two future periods under the representative concentration pathway 8.5 warming scenario: the near future (2006–40) and the late-twenty-first century (2070–99). Changes in return periods of storms affecting the state at given intensities are computed, as are wind hazards for individual counties. Other storm characteristics examined include hurricane intensity, forward speed, heading, and rate of change of the heading. The 10th, 25th, 50th, 75th, and 90th percentiles of these characteristics mostly change by less than 3% from the historical to the near future period. In the late-twenty-first century, CHAZ projects a clear upward trend in New York hurricane intensity as a consequence of increasing potential intensity and decreasing vertical wind shear in the vicinity. CHAZ also projects a decrease in translation speed and an increasing probability of approach from the east. Changes in hurricane wind hazard, however, are epistemically uncertain because of a fundamental uncertainty in CHAZ projections of New York State hurricane frequency in which frequency either increases or decreases depending on which humidity variable is used in the environmental index that controls genesis in the model. Thus, projected changes in the wind hazards are reported separately under storylines of increasing or decreasing frequency.
Abstract
This study addresses hurricane hazard to the state of New York in past, present, and future using synthetic storms generated by the Columbia Hazard model (CHAZ) and climate inputs from phase 5 of the Coupled Model Intercomparison Project (CMIP5), in conjunction with historical observations. The projected influence of anthropogenic climate change on future hazard is quantified by the normalized differences in statistics of hurricane hazard between the recent historical period (1951–2005) and two future periods under the representative concentration pathway 8.5 warming scenario: the near future (2006–40) and the late-twenty-first century (2070–99). Changes in return periods of storms affecting the state at given intensities are computed, as are wind hazards for individual counties. Other storm characteristics examined include hurricane intensity, forward speed, heading, and rate of change of the heading. The 10th, 25th, 50th, 75th, and 90th percentiles of these characteristics mostly change by less than 3% from the historical to the near future period. In the late-twenty-first century, CHAZ projects a clear upward trend in New York hurricane intensity as a consequence of increasing potential intensity and decreasing vertical wind shear in the vicinity. CHAZ also projects a decrease in translation speed and an increasing probability of approach from the east. Changes in hurricane wind hazard, however, are epistemically uncertain because of a fundamental uncertainty in CHAZ projections of New York State hurricane frequency in which frequency either increases or decreases depending on which humidity variable is used in the environmental index that controls genesis in the model. Thus, projected changes in the wind hazards are reported separately under storylines of increasing or decreasing frequency.
Abstract
Determining the contribution of urbanization to extreme high-temperature events is essential to the coordinated development of Beijing, Tianjin, and Hebei (BTH). Based on the dynamic data of land-use change in every 5 years, this study uses the coupled WRF–Building Effect Parameterization/Building Energy Model (BEP/BEM) at 1-km grid spacing to quantify the contribution of BTH urbanization to the intensity and frequency of hourly extreme high-temperature events in summer. From 1990 to 2015, extreme events over Beijing and its south increased by ∼1.5°–2°C in intensity and by 50–100 h in frequency, both of which were even higher in central Beijing and Shijiazhuang. The increases of multiyear average urbanization contribution ratios to the intensity and frequency reached 3.3% and 51.6% at the 99% confidence level (p < 0.01) from 1990 to 2015, respectively. The corresponding contributions increased 1.8 and 1.2 times more significantly in the megacities (i.e., Beijing, Tianjin, and Shijiazhuang) than small and medium-sized cities. Therefore, the rapid urbanization has substantially enhanced the extreme high-temperature events in BTH. It is necessary to limit the urbanization growth rate and implement effective adaptation and mitigation strategies to sustain BTH development.
Abstract
Determining the contribution of urbanization to extreme high-temperature events is essential to the coordinated development of Beijing, Tianjin, and Hebei (BTH). Based on the dynamic data of land-use change in every 5 years, this study uses the coupled WRF–Building Effect Parameterization/Building Energy Model (BEP/BEM) at 1-km grid spacing to quantify the contribution of BTH urbanization to the intensity and frequency of hourly extreme high-temperature events in summer. From 1990 to 2015, extreme events over Beijing and its south increased by ∼1.5°–2°C in intensity and by 50–100 h in frequency, both of which were even higher in central Beijing and Shijiazhuang. The increases of multiyear average urbanization contribution ratios to the intensity and frequency reached 3.3% and 51.6% at the 99% confidence level (p < 0.01) from 1990 to 2015, respectively. The corresponding contributions increased 1.8 and 1.2 times more significantly in the megacities (i.e., Beijing, Tianjin, and Shijiazhuang) than small and medium-sized cities. Therefore, the rapid urbanization has substantially enhanced the extreme high-temperature events in BTH. It is necessary to limit the urbanization growth rate and implement effective adaptation and mitigation strategies to sustain BTH development.
Abstract
The mesoscale vortex (MV) is an important rain-producing system. In this study, the reanalysis data and satellite precipitation products are used to classify MVs into three categories: mesoscale convective vortex (MCV), mesoscale stratiform vortex (MSV), and mesoscale dry vortex (MDV). Then, these three categories of midlevel MVs in China from 2007 to 2016 are investigated. A total of 21 053 MVs are obtained. Most MVs form in the northwest of parent convection, and 45% of MVs generate secondary convection. The Tibetan Plateau is the main MV source region. Steered by the westerlies, MVs mainly move eastward. MCV is active in summer, MDV in winter, and MSV in spring and autumn. MCV diurnal variations are closely related to local topography, and MDVs mainly form around midnight. Composite analyses show that MCVs form near the high-value center of convective available potential energy at the development stage of parent convection. The composite MCV forms near the low pressure trough and the thermal ridge at 500 hPa, and a low-level jet exists to the south of the MCV center. At the initiation and maturity stages of MCV, strong convergence and divergence respectively exist at low levels and 400 hPa. The vortex circulation mainly locates near 500 hPa. Above the vortex is a warm core associated with the latent heat release, and below is a cold anomaly related to the cold pool. In the downshear region, there is strong low-level convergence and ascending motion, higher humidity, and greater latent heat release, which favor the formation of secondary convection.
Abstract
The mesoscale vortex (MV) is an important rain-producing system. In this study, the reanalysis data and satellite precipitation products are used to classify MVs into three categories: mesoscale convective vortex (MCV), mesoscale stratiform vortex (MSV), and mesoscale dry vortex (MDV). Then, these three categories of midlevel MVs in China from 2007 to 2016 are investigated. A total of 21 053 MVs are obtained. Most MVs form in the northwest of parent convection, and 45% of MVs generate secondary convection. The Tibetan Plateau is the main MV source region. Steered by the westerlies, MVs mainly move eastward. MCV is active in summer, MDV in winter, and MSV in spring and autumn. MCV diurnal variations are closely related to local topography, and MDVs mainly form around midnight. Composite analyses show that MCVs form near the high-value center of convective available potential energy at the development stage of parent convection. The composite MCV forms near the low pressure trough and the thermal ridge at 500 hPa, and a low-level jet exists to the south of the MCV center. At the initiation and maturity stages of MCV, strong convergence and divergence respectively exist at low levels and 400 hPa. The vortex circulation mainly locates near 500 hPa. Above the vortex is a warm core associated with the latent heat release, and below is a cold anomaly related to the cold pool. In the downshear region, there is strong low-level convergence and ascending motion, higher humidity, and greater latent heat release, which favor the formation of secondary convection.
Abstract
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 6 different catchments, this study presents air temperature variability in different glacierized and 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 and dry northwestern Tibetan Plateau and the lowest LRs located on the warm and 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.
Abstract
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 6 different catchments, this study presents air temperature variability in different glacierized and 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 and dry northwestern Tibetan Plateau and the lowest LRs located on the warm and 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.
Abstract
Anomalous sea levels along the mid-Atlantic and South Atlantic coasts of the United States are often linked to atmosphere–ocean dynamics, remote- and local-scale forcing, and other factors linked to cyclone passage, winds, waves, and storm surge. Herein, we examine sea level variability along the U.S. Atlantic coast through satellite altimeter and coastal tide gauge data within the context of synoptic-scale weather pattern forcing. Altimetry data, derived from sea level anomaly (SLA) data between 1993 and 2019, were compared with self-organizing map (SOM)-based atmospheric circulation and surface wind field categorizations to reveal spatiotemporal patterns and their interrelationships with high-water-level conditions at tide gauges. Regional elevated sea level patterns and variability were strongly associated with synergistic patterns of atmospheric circulation and wind. Recurring atmospheric patterns associated with high-tide flooding events and flood risk were identified, as were specific regional oceanographic variability patterns of SLA response. The incorporation of combined metrics of wind and circulation patterns further isolate atmospheric drivers of high-tide flood events and may have particular significance for predicting future flood events over multiple spatial and temporal scales.
Significance Statement
Mean sea level and minor to moderate coastal flood events, also called blue-sky or high-tide floods, are increasing along many U.S. coastlines. While the drivers of such events are numerous, here we identified key contributing weather patterns and environmental factors linked to increased risk of regional and local high-water conditions along the Atlantic coast. Our results indicate that the predictability of elevated sea levels and high-tide floods is highly dependent upon atmospheric drivers including wind and circulation patterns and, if applied in a tested modeling framework, may prove useful for predicting future floods at various time scales.
Abstract
Anomalous sea levels along the mid-Atlantic and South Atlantic coasts of the United States are often linked to atmosphere–ocean dynamics, remote- and local-scale forcing, and other factors linked to cyclone passage, winds, waves, and storm surge. Herein, we examine sea level variability along the U.S. Atlantic coast through satellite altimeter and coastal tide gauge data within the context of synoptic-scale weather pattern forcing. Altimetry data, derived from sea level anomaly (SLA) data between 1993 and 2019, were compared with self-organizing map (SOM)-based atmospheric circulation and surface wind field categorizations to reveal spatiotemporal patterns and their interrelationships with high-water-level conditions at tide gauges. Regional elevated sea level patterns and variability were strongly associated with synergistic patterns of atmospheric circulation and wind. Recurring atmospheric patterns associated with high-tide flooding events and flood risk were identified, as were specific regional oceanographic variability patterns of SLA response. The incorporation of combined metrics of wind and circulation patterns further isolate atmospheric drivers of high-tide flood events and may have particular significance for predicting future flood events over multiple spatial and temporal scales.
Significance Statement
Mean sea level and minor to moderate coastal flood events, also called blue-sky or high-tide floods, are increasing along many U.S. coastlines. While the drivers of such events are numerous, here we identified key contributing weather patterns and environmental factors linked to increased risk of regional and local high-water conditions along the Atlantic coast. Our results indicate that the predictability of elevated sea levels and high-tide floods is highly dependent upon atmospheric drivers including wind and circulation patterns and, if applied in a tested modeling framework, may prove useful for predicting future floods at various time scales.
Abstract
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 (EID) 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 indices 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, that is, 1951–84 (stage I), 1985–97 (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.
Significance Statement
In this paper, we develop a drought intensity formula, the maximum intensity of drought, based on the “extreme” intensity–duration theory. The maximum intensity of drought was then calculated and selected as an annual drought intensity to analyze the drought characteristics in North China. We found that the annual drought intensity better captured the extremity and the patterns of drought process than that obtained with single indices and comprehensive indices. The results show a decreasing trend of drought in North China after 1998.
Abstract
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 (EID) 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 indices 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, that is, 1951–84 (stage I), 1985–97 (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.
Significance Statement
In this paper, we develop a drought intensity formula, the maximum intensity of drought, based on the “extreme” intensity–duration theory. The maximum intensity of drought was then calculated and selected as an annual drought intensity to analyze the drought characteristics in North China. We found that the annual drought intensity better captured the extremity and the patterns of drought process than that obtained with single indices and comprehensive indices. The results show a decreasing trend of drought in North China after 1998.
Abstract
Understanding the connections between latent heating from precipitation and cloud radiative effects is essential for accurately parameterizing cross-scale links between cloud microphysics and global energy and water cycles in climate models. Although commonly examined separately, this study adopts two cloud impact parameters (CIPs), the surface radiative cooling efficiency Rc and atmospheric radiative heating efficiency Rh , that explicitly couple cloud radiative effects and precipitation to characterize how efficiently precipitating cloud systems influence the energy budget and water cycle using A-Train observations and two reanalyses. These CIPs exhibit distinct global distributions that suggest cloud energy and water cycle coupling are highly dependent on cloud regime. The dynamic regime ω 500 controls the sign of Rh , whereas column water vapor (CWV) appears to be the larger control on the magnitude. The magnitude of Rc is highly coupled to the dynamic regime. Observations show that clouds cool the surface very efficiently per unit rainfall at both low and high sea surface temperature (SST) and CWV, but reanalyses only capture the former. Reanalyses fail to simulate strong Rh and moderate Rc in deep convection environments but produce stronger Rc and Rh than observations in shallow, warm rain systems in marine stratocumulus regions. Although reanalyses generate fairly similar climatologies in the frequency of environmental states, the response of Rc and Rh to SST and CWV results in systematic differences in zonal and meridional gradients of cloud atmospheric heating and surface cooling relative to A-Train observations that may have significant implications for global circulations and cloud feedbacks.
Significance Statement
Studying climate change requires understanding coupled interactions between clouds, precipitation, and their environment. Here we calculate two parameters to reveal how efficiently clouds can heat the atmosphere or cool the surface per unit rain. The satellite observations and reanalyses show similar global patterns, but there are some differences in areas of deep convection and low cloud regions. Examination of these parameters as a function of their environment shows that reanalyses cool the atmosphere too much per unit rain in environments with low sea surface temperatures and water vapor. Vertical velocity determines whether clouds heat or cool the atmosphere. Both observations and reanalyses suggest that water vapor is the stronger control on how much clouds heat the atmosphere per unit rain.
Abstract
Understanding the connections between latent heating from precipitation and cloud radiative effects is essential for accurately parameterizing cross-scale links between cloud microphysics and global energy and water cycles in climate models. Although commonly examined separately, this study adopts two cloud impact parameters (CIPs), the surface radiative cooling efficiency Rc and atmospheric radiative heating efficiency Rh , that explicitly couple cloud radiative effects and precipitation to characterize how efficiently precipitating cloud systems influence the energy budget and water cycle using A-Train observations and two reanalyses. These CIPs exhibit distinct global distributions that suggest cloud energy and water cycle coupling are highly dependent on cloud regime. The dynamic regime ω 500 controls the sign of Rh , whereas column water vapor (CWV) appears to be the larger control on the magnitude. The magnitude of Rc is highly coupled to the dynamic regime. Observations show that clouds cool the surface very efficiently per unit rainfall at both low and high sea surface temperature (SST) and CWV, but reanalyses only capture the former. Reanalyses fail to simulate strong Rh and moderate Rc in deep convection environments but produce stronger Rc and Rh than observations in shallow, warm rain systems in marine stratocumulus regions. Although reanalyses generate fairly similar climatologies in the frequency of environmental states, the response of Rc and Rh to SST and CWV results in systematic differences in zonal and meridional gradients of cloud atmospheric heating and surface cooling relative to A-Train observations that may have significant implications for global circulations and cloud feedbacks.
Significance Statement
Studying climate change requires understanding coupled interactions between clouds, precipitation, and their environment. Here we calculate two parameters to reveal how efficiently clouds can heat the atmosphere or cool the surface per unit rain. The satellite observations and reanalyses show similar global patterns, but there are some differences in areas of deep convection and low cloud regions. Examination of these parameters as a function of their environment shows that reanalyses cool the atmosphere too much per unit rain in environments with low sea surface temperatures and water vapor. Vertical velocity determines whether clouds heat or cool the atmosphere. Both observations and reanalyses suggest that water vapor is the stronger control on how much clouds heat the atmosphere per unit rain.
Abstract
Extreme heat is annually the deadliest weather hazard in the United States 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 southern Florida (i.e., Daytona Beach, Tampa, Miami, and Key West) but exhibit no conclusive relationship with urbanization changes. Danger (103°–124°F; 39.4°–51.1°C) HI and high (>88°F; 31.1°C) 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.
Significance Statement
Extreme heat is the deadliest U.S. weather hazard. Although Florida is known for its warm and humid climate, it is not immune from heat stress (combined temperature and humidity) impacts on human health, particularly given its older population and prevalence of outdoor (e.g., agriculture) work. We analyze summer trends in two heat stress metrics at eight Florida cities since 1950. Results show that heat stress is increasing significantly, particularly at coastal locations in central and southern Florida and at night. The number of dangerous heat stress days per summer is also increasing across Florida, especially since 2000. Our analysis emphasizes that despite some acclimation, Florida is still susceptible to a serious escalation in extreme heat as the climate warms.
Abstract
Extreme heat is annually the deadliest weather hazard in the United States 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 southern Florida (i.e., Daytona Beach, Tampa, Miami, and Key West) but exhibit no conclusive relationship with urbanization changes. Danger (103°–124°F; 39.4°–51.1°C) HI and high (>88°F; 31.1°C) 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.
Significance Statement
Extreme heat is the deadliest U.S. weather hazard. Although Florida is known for its warm and humid climate, it is not immune from heat stress (combined temperature and humidity) impacts on human health, particularly given its older population and prevalence of outdoor (e.g., agriculture) work. We analyze summer trends in two heat stress metrics at eight Florida cities since 1950. Results show that heat stress is increasing significantly, particularly at coastal locations in central and southern Florida and at night. The number of dangerous heat stress days per summer is also increasing across Florida, especially since 2000. Our analysis emphasizes that despite some acclimation, Florida is still susceptible to a serious escalation in extreme heat as the climate warms.
Abstract
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 canopy 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 an 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 summertime urban heating in coastal megacities, such as Shanghai.
Abstract
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 canopy 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 an 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 summertime urban heating in coastal megacities, such as Shanghai.
Abstract
Flooding from extreme precipitation can have major impacts on society in Alaska. Understanding how these extremes may change in the future is needed for better planning under climate change. Data on future changes in extreme precipitation over Alaska from dynamically downscaled output of two global climate models (GFDL and CCSM) were employed in this study. Threshold amounts for duration of the precipitation event (1 h, 1 day, and 30 days) and return intervals (2, 10, and 50 years) are evaluated and further downscaled onto NOAA Atlas 14. For each duration and return interval, the models’ fractional changes of threshold amounts are applied to the Atlas 14 estimates to remove the model bias. The threshold amounts for nearly all event durations and return intervals are projected to increase from present (1979–2005) amounts to higher values in later decadal periods (2020–49, 2050–79, and 2080–99), and the percentage increases generally exceed the changes in the mean amounts. The percentage increases are comparable in the various geographical regions of Alaska, but the increases in the actual amounts are greatest in the wetter southeast. Although the downscaled GFDL model shows larger increases than the CCSM model in amounts for nearly all durations and return intervals, both models indicate that convective precipitation will become an increasingly greater fraction of the total precipitation during the warm season. The increase in the proportion of convective precipitation is consistent with the more rapid increase in extreme amounts than in mean amounts.
Abstract
Flooding from extreme precipitation can have major impacts on society in Alaska. Understanding how these extremes may change in the future is needed for better planning under climate change. Data on future changes in extreme precipitation over Alaska from dynamically downscaled output of two global climate models (GFDL and CCSM) were employed in this study. Threshold amounts for duration of the precipitation event (1 h, 1 day, and 30 days) and return intervals (2, 10, and 50 years) are evaluated and further downscaled onto NOAA Atlas 14. For each duration and return interval, the models’ fractional changes of threshold amounts are applied to the Atlas 14 estimates to remove the model bias. The threshold amounts for nearly all event durations and return intervals are projected to increase from present (1979–2005) amounts to higher values in later decadal periods (2020–49, 2050–79, and 2080–99), and the percentage increases generally exceed the changes in the mean amounts. The percentage increases are comparable in the various geographical regions of Alaska, but the increases in the actual amounts are greatest in the wetter southeast. Although the downscaled GFDL model shows larger increases than the CCSM model in amounts for nearly all durations and return intervals, both models indicate that convective precipitation will become an increasingly greater fraction of the total precipitation during the warm season. The increase in the proportion of convective precipitation is consistent with the more rapid increase in extreme amounts than in mean amounts.
