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- Author or Editor: S. C. Lee x
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Abstract
A study has been made of the growth through collision of water drops in the atmosphere. The method of superposition of flow fields obtained from the numerical solution of the Navier-Stokes equations was used for the calculations, and only inertia, gravity and drag force were considered.
The calculated linear collision efficiency is significantly less than the geometric collision efficiency between a large collector drop and a small collecting drop because of the effect of hydrodynamic forces. The linear collision efficiency is substantially higher than the geometric collision efficiency between similarly sized drops because of the wake effect.
To verify the validity of the calculations, the analytical results were compared with available experimental data. Satisfactory agreement was obtained for most drop sizes. It is concluded that in the absence of electricity and turbulence the dominant factor in the formation of precipitation is the collisional growth of similarly sized drops.
Abstract
A study has been made of the growth through collision of water drops in the atmosphere. The method of superposition of flow fields obtained from the numerical solution of the Navier-Stokes equations was used for the calculations, and only inertia, gravity and drag force were considered.
The calculated linear collision efficiency is significantly less than the geometric collision efficiency between a large collector drop and a small collecting drop because of the effect of hydrodynamic forces. The linear collision efficiency is substantially higher than the geometric collision efficiency between similarly sized drops because of the wake effect.
To verify the validity of the calculations, the analytical results were compared with available experimental data. Satisfactory agreement was obtained for most drop sizes. It is concluded that in the absence of electricity and turbulence the dominant factor in the formation of precipitation is the collisional growth of similarly sized drops.
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Abstract
The Warren-Nesbitt generator is widely used in Australia and other countries for producing a cloud seeding aerosol by burning a solution of silver iodide and sodium iodide in acetone. It is found that the particle size distribution follows a log probability law with median diameter 0.085 μ and standard deviation factor 1.47. Electron diffraction examination of the particles shows that they consist of beta silver iodide and sodium iodide. The available evidence indicates that each particle is probably a mixture of these two constituents.
Abstract
The Warren-Nesbitt generator is widely used in Australia and other countries for producing a cloud seeding aerosol by burning a solution of silver iodide and sodium iodide in acetone. It is found that the particle size distribution follows a log probability law with median diameter 0.085 μ and standard deviation factor 1.47. Electron diffraction examination of the particles shows that they consist of beta silver iodide and sodium iodide. The available evidence indicates that each particle is probably a mixture of these two constituents.
Abstract
A Terminal Doppler Weather Radar (TDWR) started operation in Hong Kong, China, in 1997 for monitoring wind shear associated with thunderstorms affecting the Hong Kong International Airport. The airport was built on land reclaimed from the sea and lies to the immediate north of the mountainous Lantau Island, which has hills rising to nearly 1000 m. Since 1997, the airport experienced a number of tropical cyclone passages, some bringing strong southerly winds across these hills. Under these conditions the TDWR captured interesting but complex flow patterns in the lower atmosphere. The TDWR Doppler velocity datasets reveal features not previously observed with conventional instruments. These include shear lines, reverse flow, small-scale vortices, streaks of low-speed flow set against a high-speed background, as well as gap-related downslope high-speed flow. Hovmöller diagrams constructed from the Doppler velocity data bring out in considerable detail periodic shedding of vortices and transient wind patterns in the wake of the hills.
Abstract
A Terminal Doppler Weather Radar (TDWR) started operation in Hong Kong, China, in 1997 for monitoring wind shear associated with thunderstorms affecting the Hong Kong International Airport. The airport was built on land reclaimed from the sea and lies to the immediate north of the mountainous Lantau Island, which has hills rising to nearly 1000 m. Since 1997, the airport experienced a number of tropical cyclone passages, some bringing strong southerly winds across these hills. Under these conditions the TDWR captured interesting but complex flow patterns in the lower atmosphere. The TDWR Doppler velocity datasets reveal features not previously observed with conventional instruments. These include shear lines, reverse flow, small-scale vortices, streaks of low-speed flow set against a high-speed background, as well as gap-related downslope high-speed flow. Hovmöller diagrams constructed from the Doppler velocity data bring out in considerable detail periodic shedding of vortices and transient wind patterns in the wake of the hills.
Abstract
The annual heat budget of the Western Hemisphere warm pool (WHWP) is explored using the output of an ocean general circulation model (OGCM) simulation. According to the analysis, the WHWP cannot be considered as a monolithic whole with a single set of dominating processes that explain its behavior. The three regions considered, namely the eastern north Pacific (ENP), the Gulf of Mexico (GoM), and the Caribbean Sea (CBN), are each unique in terms of the atmospheric and oceanic processes that dominate the corresponding heat budgets. In the ENP region, clear-sky shortwave radiation flux is responsible for the growth of the warm pool in boreal spring, while increased cloud cover in boreal summer and associated reduction in solar radiation play a crucial role for the ENP warm pool’s demise. Ocean upwelling in the Costa Rica Dome connected to surrounding areas by horizontal advection offers a persistent yearlong cooling mechanism. Over the Atlantic, the clear-sky radiation flux that increases monotonically from December to May and decreases later is largely responsible for the onset and decay of the Atlantic-side warm pool in boreal summer and fall. The CBN region is affected by upwelling and horizontal advective cooling within and away from the coastal upwelling zone off northern South America during the onset and peak phases, thus slowing down the warm pool’s development, but no evidence was found that advective heat flux divergence is important in the GoM region. Turbulent mixing is also an important cooling mechanism in the annual cycle of the WHWP, and the vertical shear at the warm pool base helps to sustain the turbulent mixing. Common to all three WHWP regions is the reduction of wind speed at the peak phase, suggestive of a convection–evaporation feedback known to be important in the Indo-Pacific warm pool dynamics.
Abstract
The annual heat budget of the Western Hemisphere warm pool (WHWP) is explored using the output of an ocean general circulation model (OGCM) simulation. According to the analysis, the WHWP cannot be considered as a monolithic whole with a single set of dominating processes that explain its behavior. The three regions considered, namely the eastern north Pacific (ENP), the Gulf of Mexico (GoM), and the Caribbean Sea (CBN), are each unique in terms of the atmospheric and oceanic processes that dominate the corresponding heat budgets. In the ENP region, clear-sky shortwave radiation flux is responsible for the growth of the warm pool in boreal spring, while increased cloud cover in boreal summer and associated reduction in solar radiation play a crucial role for the ENP warm pool’s demise. Ocean upwelling in the Costa Rica Dome connected to surrounding areas by horizontal advection offers a persistent yearlong cooling mechanism. Over the Atlantic, the clear-sky radiation flux that increases monotonically from December to May and decreases later is largely responsible for the onset and decay of the Atlantic-side warm pool in boreal summer and fall. The CBN region is affected by upwelling and horizontal advective cooling within and away from the coastal upwelling zone off northern South America during the onset and peak phases, thus slowing down the warm pool’s development, but no evidence was found that advective heat flux divergence is important in the GoM region. Turbulent mixing is also an important cooling mechanism in the annual cycle of the WHWP, and the vertical shear at the warm pool base helps to sustain the turbulent mixing. Common to all three WHWP regions is the reduction of wind speed at the peak phase, suggestive of a convection–evaporation feedback known to be important in the Indo-Pacific warm pool dynamics.
Abstract
Since drought and excessive rainfall can have significant socioeconomic impacts, it is important to have accurate high-resolution gridded datasets that can help improve analysis and forecasting of these conditions. One such widely used dataset is the Parameter-Elevation Regressions on Independent Slopes Model (PRISM). PRISM uses a digital elevation model (DEM) to obtain gridded elevation analyses and then uses a regression analysis along with approximately 15 000 surface precipitation measurements to produce a 4-km resolution daily precipitation product over the conterminous United States. The U.S. Climate Reference Network (USCRN) consists of 114 stations that take highly accurate meteorological measurements across all regions of the United States. A comparison between the USCRN and PRISM was performed using data from 2006 to 2018. There were good comparisons between the two datasets across nearly all seasons and regions; most mean daily differences were <1 mm, with most absolute daily differences ~5 mm. The most general characteristics were for a net dry bias in the PRISM data in the Southwest and a net moist bias in the southern United States. Verifying the PRISM dataset provides us with confidence it can be used with estimates of evapotranspiration, high-resolution gridded soil properties, and vegetation datasets to produce a daily gridded soil moisture product for operational use in the analyses and prediction of drought and excessive soil moisture conditions.
Abstract
Since drought and excessive rainfall can have significant socioeconomic impacts, it is important to have accurate high-resolution gridded datasets that can help improve analysis and forecasting of these conditions. One such widely used dataset is the Parameter-Elevation Regressions on Independent Slopes Model (PRISM). PRISM uses a digital elevation model (DEM) to obtain gridded elevation analyses and then uses a regression analysis along with approximately 15 000 surface precipitation measurements to produce a 4-km resolution daily precipitation product over the conterminous United States. The U.S. Climate Reference Network (USCRN) consists of 114 stations that take highly accurate meteorological measurements across all regions of the United States. A comparison between the USCRN and PRISM was performed using data from 2006 to 2018. There were good comparisons between the two datasets across nearly all seasons and regions; most mean daily differences were <1 mm, with most absolute daily differences ~5 mm. The most general characteristics were for a net dry bias in the PRISM data in the Southwest and a net moist bias in the southern United States. Verifying the PRISM dataset provides us with confidence it can be used with estimates of evapotranspiration, high-resolution gridded soil properties, and vegetation datasets to produce a daily gridded soil moisture product for operational use in the analyses and prediction of drought and excessive soil moisture conditions.
Abstract
In this paper, the prediction skills of five ensemble methods for temperature and precipitation are discussed by considering 20 yr of simulation results (from 1989 to 2008) for four regional climate models (RCMs) driven by NCEP–Department of Energy and ECMWF Interim Re-Analysis (ERA-Interim) boundary conditions. The simulation domain is the Coordinated Regional Downscaling Experiment (CORDEX) for East Asia, and the number of grid points is 197 × 233 with a 50-km horizontal resolution. Three new performance-based ensemble averaging (PEA) methods are developed in this study using 1) bias, root-mean-square errors (RMSEs) and absolute correlation (PEA_BRC), RMSE and absolute correlation (PEA_RAC), and RMSE and original correlation (PEA_ROC). The other two ensemble methods are equal-weighted averaging (EWA) and multivariate linear regression (Mul_Reg). To derive the weighting coefficients and cross validate the prediction skills of the five ensemble methods, the authors considered 15-yr and 5-yr data, respectively, from the 20-yr simulation data. Among the five ensemble methods, the Mul_Reg (EWA) method shows the best (worst) skill during the training period. The PEA_RAC and PEA_ROC methods show skills that are similar to those of Mul_Reg during the training period. However, the skills and stabilities of Mul_Reg were drastically reduced when this method was applied to the prediction period. But, the skills and stabilities of PEA_RAC were only slightly reduced in this case. As a result, PEA_RAC shows the best skill, irrespective of the seasons and variables, during the prediction period. This result confirms that the new ensemble method developed in this study, PEA_RAC, can be used for the prediction of regional climate.
Abstract
In this paper, the prediction skills of five ensemble methods for temperature and precipitation are discussed by considering 20 yr of simulation results (from 1989 to 2008) for four regional climate models (RCMs) driven by NCEP–Department of Energy and ECMWF Interim Re-Analysis (ERA-Interim) boundary conditions. The simulation domain is the Coordinated Regional Downscaling Experiment (CORDEX) for East Asia, and the number of grid points is 197 × 233 with a 50-km horizontal resolution. Three new performance-based ensemble averaging (PEA) methods are developed in this study using 1) bias, root-mean-square errors (RMSEs) and absolute correlation (PEA_BRC), RMSE and absolute correlation (PEA_RAC), and RMSE and original correlation (PEA_ROC). The other two ensemble methods are equal-weighted averaging (EWA) and multivariate linear regression (Mul_Reg). To derive the weighting coefficients and cross validate the prediction skills of the five ensemble methods, the authors considered 15-yr and 5-yr data, respectively, from the 20-yr simulation data. Among the five ensemble methods, the Mul_Reg (EWA) method shows the best (worst) skill during the training period. The PEA_RAC and PEA_ROC methods show skills that are similar to those of Mul_Reg during the training period. However, the skills and stabilities of Mul_Reg were drastically reduced when this method was applied to the prediction period. But, the skills and stabilities of PEA_RAC were only slightly reduced in this case. As a result, PEA_RAC shows the best skill, irrespective of the seasons and variables, during the prediction period. This result confirms that the new ensemble method developed in this study, PEA_RAC, can be used for the prediction of regional climate.
Abstract
A wide range of environmental applications would benefit from a dense network of air temperature observations. However, with limitations of costs, existing siting guidelines, and risk of damage, new methods are required to gain a high-resolution understanding of spatiotemporal patterns of temperature for agricultural and urban meteorological phenomena such as the urban heat island. With the launch of a new generation of low-cost sensors, it is possible to deploy a network to monitor air temperature at finer spatial resolutions. This study investigates the Aginova Sentinel Micro (ASM) sensor with a custom radiation shield (together less than USD$150) that can provide secure near-real-time air temperature data to a server utilizing existing (or user deployed) Wi-Fi networks. This makes it ideally suited for deployment where wireless communications readily exist, notably urban areas. Assessment of the performance of the ASM relative to traceable standards in a water bath and atmospheric chamber show it to have good measurement accuracy with mean errors <±0.22°C between −25° and 30°C, with a time constant in ambient air of 110 ±15 s. Subsequent field tests also showed the ASM (in the custom shield) had excellent performance (RMSE = 0.13°C) over a range of meteorological conditions relative to a traceable operational Met Office platinum resistance thermometer. These results indicate that the ASM and radiation shield are more than fit for purpose for dense network deployment in environmental monitoring applications at relatively low cost compared to existing observation techniques.
Abstract
A wide range of environmental applications would benefit from a dense network of air temperature observations. However, with limitations of costs, existing siting guidelines, and risk of damage, new methods are required to gain a high-resolution understanding of spatiotemporal patterns of temperature for agricultural and urban meteorological phenomena such as the urban heat island. With the launch of a new generation of low-cost sensors, it is possible to deploy a network to monitor air temperature at finer spatial resolutions. This study investigates the Aginova Sentinel Micro (ASM) sensor with a custom radiation shield (together less than USD$150) that can provide secure near-real-time air temperature data to a server utilizing existing (or user deployed) Wi-Fi networks. This makes it ideally suited for deployment where wireless communications readily exist, notably urban areas. Assessment of the performance of the ASM relative to traceable standards in a water bath and atmospheric chamber show it to have good measurement accuracy with mean errors <±0.22°C between −25° and 30°C, with a time constant in ambient air of 110 ±15 s. Subsequent field tests also showed the ASM (in the custom shield) had excellent performance (RMSE = 0.13°C) over a range of meteorological conditions relative to a traceable operational Met Office platinum resistance thermometer. These results indicate that the ASM and radiation shield are more than fit for purpose for dense network deployment in environmental monitoring applications at relatively low cost compared to existing observation techniques.
With the growing number and significance of urban meteorological networks (UMNs) across the world, it is becoming critical to establish a standard metadata protocol. Indeed, a review of existing UMNs indicate large variations in the quality, quantity, and availability of metadata containing technical information (i.e., equipment, communication methods) and network practices (i.e., quality assurance/quality control and data management procedures). Without such metadata, the utility of UMNs is greatly compromised. There is a need to bring together the currently disparate sets of guidelines to ensure informed and well-documented future deployments. This should significantly improve the quality, and therefore the applicability, of the high-resolution data available from such networks. Here, the first metadata protocol for UMNs is proposed, drawing on current recommendations for urban climate stations and identified best practice in existing networks.
With the growing number and significance of urban meteorological networks (UMNs) across the world, it is becoming critical to establish a standard metadata protocol. Indeed, a review of existing UMNs indicate large variations in the quality, quantity, and availability of metadata containing technical information (i.e., equipment, communication methods) and network practices (i.e., quality assurance/quality control and data management procedures). Without such metadata, the utility of UMNs is greatly compromised. There is a need to bring together the currently disparate sets of guidelines to ensure informed and well-documented future deployments. This should significantly improve the quality, and therefore the applicability, of the high-resolution data available from such networks. Here, the first metadata protocol for UMNs is proposed, drawing on current recommendations for urban climate stations and identified best practice in existing networks.
