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Abstract
Physical storm characteristics during the operational period of the Santa Barbara Cloud Seeding Project have been studied. It is shown that the vertical storm structure, particularly the depth of the low-level convective layer, is of importance in determining (1) the area distribution of precipitation, (2) the transport of seeding material from the ground to the nucleation levels, and (3) the existence of supercooled liquid water at nucleation levels. Item (1) above influences the correlation between target and control precipitation amounts, and items (2) and (3) influence the effective seeding of the storm. The seeded and unseeded storms of the Project have been treated using these concepts in order to investigate their influence on the inconclusive statistical results of the Project.
On the basis of qualitative seedability criteria, it is estimated that approximately one-half of the precipitation in the Project period occurred under relatively poor seeding conditions. This was determined by classifying storms into convective and stable flow types. It is also shown that the convective and stable cases have differing orographic precipitation characteristics and that, as a consequence, the target-control relationship is a function of vertical storm stability.
The study suggests that the possibility of detecting seeding effects can be improved by elimination of poor seeding cases through development of better seedability critera and by stratifying target-control relationships according to storm type. Also indicated is a need for improved understanding of natural rainfall variations before substantial progress can be made in detecting detailed variations caused by seeding.
Abstract
Physical storm characteristics during the operational period of the Santa Barbara Cloud Seeding Project have been studied. It is shown that the vertical storm structure, particularly the depth of the low-level convective layer, is of importance in determining (1) the area distribution of precipitation, (2) the transport of seeding material from the ground to the nucleation levels, and (3) the existence of supercooled liquid water at nucleation levels. Item (1) above influences the correlation between target and control precipitation amounts, and items (2) and (3) influence the effective seeding of the storm. The seeded and unseeded storms of the Project have been treated using these concepts in order to investigate their influence on the inconclusive statistical results of the Project.
On the basis of qualitative seedability criteria, it is estimated that approximately one-half of the precipitation in the Project period occurred under relatively poor seeding conditions. This was determined by classifying storms into convective and stable flow types. It is also shown that the convective and stable cases have differing orographic precipitation characteristics and that, as a consequence, the target-control relationship is a function of vertical storm stability.
The study suggests that the possibility of detecting seeding effects can be improved by elimination of poor seeding cases through development of better seedability critera and by stratifying target-control relationships according to storm type. Also indicated is a need for improved understanding of natural rainfall variations before substantial progress can be made in detecting detailed variations caused by seeding.
Abstract
This study presents the development and testing of two statistical models that simulate tornado potential and wind speed. This study reports on the first-ever development of two multiple regression–based models to assist warning forecasters in statistically simulating tornado probability and tornado wind speed in a diagnostic manner based on radar-observed tornado signature attributes and one environmental parameter. Based on a robust database, the radar-based storm-scale circulation attributes (strength, height above ground, clarity) combine with the effective-layer significant tornado parameter to establish a tornado probability. The second model adds the categorical presence (absence) of a tornadic debris signature to derive the tornado wind speed. While the fits of these models are considered somewhat modest, their regression coefficients generally offer physical consistency, based on findings from previous research. Furthermore, simulating these models on an independent dataset and other past cases featured in previous research reveals encouraging signals for accurately identifying higher potential for tornadoes. This statistical application using large-sample-size datasets can serve as a first step to streamlining the process of reproducibly quantifying tornado threats by service-providing organizations in a diagnostic manner, encouraging consistency in messaging scientifically sound information for the protection of life and property.
Abstract
This study presents the development and testing of two statistical models that simulate tornado potential and wind speed. This study reports on the first-ever development of two multiple regression–based models to assist warning forecasters in statistically simulating tornado probability and tornado wind speed in a diagnostic manner based on radar-observed tornado signature attributes and one environmental parameter. Based on a robust database, the radar-based storm-scale circulation attributes (strength, height above ground, clarity) combine with the effective-layer significant tornado parameter to establish a tornado probability. The second model adds the categorical presence (absence) of a tornadic debris signature to derive the tornado wind speed. While the fits of these models are considered somewhat modest, their regression coefficients generally offer physical consistency, based on findings from previous research. Furthermore, simulating these models on an independent dataset and other past cases featured in previous research reveals encouraging signals for accurately identifying higher potential for tornadoes. This statistical application using large-sample-size datasets can serve as a first step to streamlining the process of reproducibly quantifying tornado threats by service-providing organizations in a diagnostic manner, encouraging consistency in messaging scientifically sound information for the protection of life and property.
Abstract
Satellite meteorology is a relatively new branch of the atmospheric sciences. The field emerged in the late 1950s during the Cold War and built on the advances in rocketry after World War II. In less than 70 years, satellite observations have transformed the way scientists observe and study Earth. This paper discusses some of the key advances in our understanding of the energy and water cycles, weather forecasting, and atmospheric composition enabled by satellite observations. While progress truly has been an international achievement, in accord with a monograph observing the centennial of the American Meteorological Society, as well as limited space, the emphasis of this chapter is on the U.S. satellite effort.
Abstract
Satellite meteorology is a relatively new branch of the atmospheric sciences. The field emerged in the late 1950s during the Cold War and built on the advances in rocketry after World War II. In less than 70 years, satellite observations have transformed the way scientists observe and study Earth. This paper discusses some of the key advances in our understanding of the energy and water cycles, weather forecasting, and atmospheric composition enabled by satellite observations. While progress truly has been an international achievement, in accord with a monograph observing the centennial of the American Meteorological Society, as well as limited space, the emphasis of this chapter is on the U.S. satellite effort.
Abstract
The 6085±10 km radius of Venus deduced from combining observations made with the Venera 4 and Mariner 5 space probes appears to be incompatible with the 6050±5 km radius determined from earth-based radar measurements.
Abstract
The 6085±10 km radius of Venus deduced from combining observations made with the Venera 4 and Mariner 5 space probes appears to be incompatible with the 6050±5 km radius determined from earth-based radar measurements.
Abstract
Recent developments to the Local-scale Urban Meteorological Parameterization Scheme (LUMPS), a simple model able to simulate the urban energy balance, are presented. The major development is the coupling of LUMPS to the Net All-Wave Radiation Parameterization (NARP). Other enhancements include that the model now accounts for the changing availability of water at the surface, seasonal variations of active vegetation, and the anthropogenic heat flux, while maintaining the need for only commonly available meteorological observations and basic surface characteristics. The incoming component of the longwave radiation (L↓) in NARP is improved through a simple relation derived using cloud cover observations from a ceilometer collected in central London, England. The new L↓ formulation is evaluated with two independent multiyear datasets (Łódź, Poland, and Baltimore, Maryland) and compared with alternatives that include the original NARP and a simpler one using the National Climatic Data Center cloud observation database as input. The performance for the surface energy balance fluxes is assessed using a 2-yr dataset (Łódź). Results have an overall RMSE < 34 W m−2 for all surface energy balance fluxes over the 2-yr period when using L↓ as forcing, and RMSE < 43 W m−2 for all seasons in 2002 with all other options implemented to model L↓.
Abstract
Recent developments to the Local-scale Urban Meteorological Parameterization Scheme (LUMPS), a simple model able to simulate the urban energy balance, are presented. The major development is the coupling of LUMPS to the Net All-Wave Radiation Parameterization (NARP). Other enhancements include that the model now accounts for the changing availability of water at the surface, seasonal variations of active vegetation, and the anthropogenic heat flux, while maintaining the need for only commonly available meteorological observations and basic surface characteristics. The incoming component of the longwave radiation (L↓) in NARP is improved through a simple relation derived using cloud cover observations from a ceilometer collected in central London, England. The new L↓ formulation is evaluated with two independent multiyear datasets (Łódź, Poland, and Baltimore, Maryland) and compared with alternatives that include the original NARP and a simpler one using the National Climatic Data Center cloud observation database as input. The performance for the surface energy balance fluxes is assessed using a 2-yr dataset (Łódź). Results have an overall RMSE < 34 W m−2 for all surface energy balance fluxes over the 2-yr period when using L↓ as forcing, and RMSE < 43 W m−2 for all seasons in 2002 with all other options implemented to model L↓.
Abstract
A historical water clarity index (K d index or KDI) was developed through the use of satellite-derived and validated diffuse light attenuation (K d ; m−1) for each of the Great Lakes (and subbasins) on a daily level from 1998 to 2015. A statistical regionalization was performed with monthly level KDI using k-means clustering to subdivide the Great Lakes into regions with similar temporal variability in water clarity. The KDI was then used to assess the relationship between water clarity and atmospheric circulation patterns and stream discharge. An artificial neural-network-based self-organized map data reduction technique was used to classify atmospheric patterns using four atmospheric variables: mean sea level pressure, 500-hPa geopotential heights, zonal and meridional components of the wind at 10 m, and 850-hPa temperature. Stream discharge was found to have the strongest relationship with KDI, suggesting that sediments and dissolved matter from land runoffs are the key factors linking the atmosphere to water clarity in the Great Lakes. Although generally lower in magnitude than stream discharge, atmospheric circulation patterns associated with increased precipitation tended to have stronger positive correlations with KDI. With no long-range forecasts of stream discharge, the strong relationship between atmospheric circulation patterns and stream discharge may provide an avenue to more accurately model water clarity on a subseasonal-to-seasonal time scale.
Abstract
A historical water clarity index (K d index or KDI) was developed through the use of satellite-derived and validated diffuse light attenuation (K d ; m−1) for each of the Great Lakes (and subbasins) on a daily level from 1998 to 2015. A statistical regionalization was performed with monthly level KDI using k-means clustering to subdivide the Great Lakes into regions with similar temporal variability in water clarity. The KDI was then used to assess the relationship between water clarity and atmospheric circulation patterns and stream discharge. An artificial neural-network-based self-organized map data reduction technique was used to classify atmospheric patterns using four atmospheric variables: mean sea level pressure, 500-hPa geopotential heights, zonal and meridional components of the wind at 10 m, and 850-hPa temperature. Stream discharge was found to have the strongest relationship with KDI, suggesting that sediments and dissolved matter from land runoffs are the key factors linking the atmosphere to water clarity in the Great Lakes. Although generally lower in magnitude than stream discharge, atmospheric circulation patterns associated with increased precipitation tended to have stronger positive correlations with KDI. With no long-range forecasts of stream discharge, the strong relationship between atmospheric circulation patterns and stream discharge may provide an avenue to more accurately model water clarity on a subseasonal-to-seasonal time scale.
The Atmospheric Science Education Program (ASEP) established in 1986 at Purdue University had two components: (1) To conduct a summer program for teachers on topics in atmospheric science; and (2) To develop educational materials for teaching atmospheric science to grades five through nine.
The ASEP Summer Program for Teachers was conducted at Purdue University in July 1987 for selected Indiana teachers. Its purpose was to help teachers that teach science in grades five through nine to incorporate atmospheric science topics into their school curricula. The teachers participated in a four-week program that included lectures, laboratory sessions, educational applications seminars, field trips, and guest speakers.
The ASEP staff also developed a series of videotapes and an accompanying set of instructional booklets for students and teachers. These materials were designed to reach a nationwide audience of students and teachers of science so they could incorporate atmospheric-related activities into the general science classroom. The participating teachers in the summer program provided input on the suitability (for the targeted school grades) of these materials, which will become available in late 1988.
Follow-up visitations were made by ASEP staff to the schools of the summer participants to determine the impact of the summer program and to assist the teachers with implementation of atmospheric science into their science classrooms. These visitations and other correspondence with the participating teachers have revealed that the teachers are actively adapting the educational materials and components of the summer program instruction into their science curricula, as well as conducting in-service training for other teachers in their own school districts and at state science-teachers' meetings.
The Atmospheric Science Education Program (ASEP) established in 1986 at Purdue University had two components: (1) To conduct a summer program for teachers on topics in atmospheric science; and (2) To develop educational materials for teaching atmospheric science to grades five through nine.
The ASEP Summer Program for Teachers was conducted at Purdue University in July 1987 for selected Indiana teachers. Its purpose was to help teachers that teach science in grades five through nine to incorporate atmospheric science topics into their school curricula. The teachers participated in a four-week program that included lectures, laboratory sessions, educational applications seminars, field trips, and guest speakers.
The ASEP staff also developed a series of videotapes and an accompanying set of instructional booklets for students and teachers. These materials were designed to reach a nationwide audience of students and teachers of science so they could incorporate atmospheric-related activities into the general science classroom. The participating teachers in the summer program provided input on the suitability (for the targeted school grades) of these materials, which will become available in late 1988.
Follow-up visitations were made by ASEP staff to the schools of the summer participants to determine the impact of the summer program and to assist the teachers with implementation of atmospheric science into their science classrooms. These visitations and other correspondence with the participating teachers have revealed that the teachers are actively adapting the educational materials and components of the summer program instruction into their science curricula, as well as conducting in-service training for other teachers in their own school districts and at state science-teachers' meetings.
Abstract
The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on 27 November 1997, and data from all the instruments first became available approximately 30 days after the launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms, and applications of these results to areas such as data assimilation and model initialization. The TRMM Microwave Imager (TMI) calibration has been corrected and verified to account for a small source of radiation leaking into the TMI receiver. The precipitation radar calibration has been adjusted upward slightly (by 0.6 dBZ) to match better the ground reference targets; the visible and infrared sensor calibration remains largely unchanged. Two versions of the TRMM rainfall algorithms are discussed. The at-launch (version 4) algorithms showed differences of 40% when averaged over the global Tropics over 30-day periods. The improvements to the rainfall algorithms that were undertaken after launch are presented, and intercomparisons of these products (version 5) show agreement improving to 24% for global tropical monthly averages. The ground-based radar rainfall product generation is discussed. Quality-control issues have delayed the routine production of these products until the summer of 2000, but comparisons of TRMM products with early versions of the ground validation products as well as with rain gauge network data suggest that uncertainties among the TRMM algorithms are of approximately the same magnitude as differences between TRMM products and ground-based rainfall estimates. The TRMM field experiment program is discussed to describe active areas of measurements and plans to use these data for further algorithm improvements. In addition to the many papers in this special issue, results coming from the analysis of TRMM products to study the diurnal cycle, the climatological description of the vertical profile of precipitation, storm types, and the distribution of shallow convection, as well as advances in data assimilation of moisture and model forecast improvements using TRMM data, are discussed in a companion TRMM special issue in the Journal of Climate (1 December 2000, Vol. 13, No. 23).
Abstract
The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on 27 November 1997, and data from all the instruments first became available approximately 30 days after the launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms, and applications of these results to areas such as data assimilation and model initialization. The TRMM Microwave Imager (TMI) calibration has been corrected and verified to account for a small source of radiation leaking into the TMI receiver. The precipitation radar calibration has been adjusted upward slightly (by 0.6 dBZ) to match better the ground reference targets; the visible and infrared sensor calibration remains largely unchanged. Two versions of the TRMM rainfall algorithms are discussed. The at-launch (version 4) algorithms showed differences of 40% when averaged over the global Tropics over 30-day periods. The improvements to the rainfall algorithms that were undertaken after launch are presented, and intercomparisons of these products (version 5) show agreement improving to 24% for global tropical monthly averages. The ground-based radar rainfall product generation is discussed. Quality-control issues have delayed the routine production of these products until the summer of 2000, but comparisons of TRMM products with early versions of the ground validation products as well as with rain gauge network data suggest that uncertainties among the TRMM algorithms are of approximately the same magnitude as differences between TRMM products and ground-based rainfall estimates. The TRMM field experiment program is discussed to describe active areas of measurements and plans to use these data for further algorithm improvements. In addition to the many papers in this special issue, results coming from the analysis of TRMM products to study the diurnal cycle, the climatological description of the vertical profile of precipitation, storm types, and the distribution of shallow convection, as well as advances in data assimilation of moisture and model forecast improvements using TRMM data, are discussed in a companion TRMM special issue in the Journal of Climate (1 December 2000, Vol. 13, No. 23).
Three spectrally broadband measurement sets are presently being used for earth radiation budget (ERB) studies. These are the Nimbus-6 ERB (July 1975 to June 1978), the Nimbus-7 ERB (November 1978 to the present), and the Earth Radiation Budget Experiment (ERBE) (November 1984 to present). The measurements yield the incident solar irradiance, absorbed solar energy, outgoing longwave and net radiation. The Nimbus-7 started an accurate record of the solar constant in November 1978, while a nearly continuous record of the earth's radiation budget began in July 1975 with the Nimbus-6. Both the Nimbus-6 and -7 products have, in recent years, been reprocessed with improved processing and calibration algorithms so that the entire dataset can be considered as new. However, because of the use of different calibration and processing procedures, the three datasets for some purposes must be considered as piecewise continuous. Nevertheless, the data have been used in many important climate studies. The Nimbus-7 solar measurements indicate that the sun is a low-level variable star and that the mean annual solar energy just outside the earth's atmosphere was about 0.1% lower in 1984 than in 1979 and 1991. Further, the 9 years of Nimbus-7 ERB measurements show the earth's mean annual energy budget to be stable at the 0.2% level with apparently real changes in the annual emitted longwave at the 0.1% to 0.2% level that are associated with changes in the surface temperature. Other studies deal with the cooling and warming effects of clouds, interregional energy transport, and interannual variations. Our understanding of the sensors and how to derive an accurate mean radiation budget from the measurements has slowly improved over the years. But to date, there has been no consensus on the use of consistent calibration and processing procedures to permit quantitatively consistent analyses across the Nimbus-6, -7, and ERBE products. This report describes some successes and lessons learned during the Nimbus ERB program and the compatibility of the Nimbus and ERBE products.
Three spectrally broadband measurement sets are presently being used for earth radiation budget (ERB) studies. These are the Nimbus-6 ERB (July 1975 to June 1978), the Nimbus-7 ERB (November 1978 to the present), and the Earth Radiation Budget Experiment (ERBE) (November 1984 to present). The measurements yield the incident solar irradiance, absorbed solar energy, outgoing longwave and net radiation. The Nimbus-7 started an accurate record of the solar constant in November 1978, while a nearly continuous record of the earth's radiation budget began in July 1975 with the Nimbus-6. Both the Nimbus-6 and -7 products have, in recent years, been reprocessed with improved processing and calibration algorithms so that the entire dataset can be considered as new. However, because of the use of different calibration and processing procedures, the three datasets for some purposes must be considered as piecewise continuous. Nevertheless, the data have been used in many important climate studies. The Nimbus-7 solar measurements indicate that the sun is a low-level variable star and that the mean annual solar energy just outside the earth's atmosphere was about 0.1% lower in 1984 than in 1979 and 1991. Further, the 9 years of Nimbus-7 ERB measurements show the earth's mean annual energy budget to be stable at the 0.2% level with apparently real changes in the annual emitted longwave at the 0.1% to 0.2% level that are associated with changes in the surface temperature. Other studies deal with the cooling and warming effects of clouds, interregional energy transport, and interannual variations. Our understanding of the sensors and how to derive an accurate mean radiation budget from the measurements has slowly improved over the years. But to date, there has been no consensus on the use of consistent calibration and processing procedures to permit quantitatively consistent analyses across the Nimbus-6, -7, and ERBE products. This report describes some successes and lessons learned during the Nimbus ERB program and the compatibility of the Nimbus and ERBE products.
Abstract
A coupled system of wind, wind wave, and coastal circulation models has been implemented for southern Louisiana and Mississippi to simulate riverine flows, tides, wind waves, and hurricane storm surge in the region. The system combines the NOAA Hurricane Research Division Wind Analysis System (H*WIND) and the Interactive Objective Kinematic Analysis (IOKA) kinematic wind analyses, the Wave Model (WAM) offshore and Steady-State Irregular Wave (STWAVE) nearshore wind wave models, and the Advanced Circulation (ADCIRC) basin to channel-scale unstructured grid circulation model. The system emphasizes a high-resolution (down to 50 m) representation of the geometry, bathymetry, and topography; nonlinear coupling of all processes including wind wave radiation stress-induced set up; and objective specification of frictional parameters based on land-cover databases and commonly used parameters. Riverine flows and tides are validated for no storm conditions, while winds, wind waves, hydrographs, and high water marks are validated for Hurricanes Katrina and Rita.
Abstract
A coupled system of wind, wind wave, and coastal circulation models has been implemented for southern Louisiana and Mississippi to simulate riverine flows, tides, wind waves, and hurricane storm surge in the region. The system combines the NOAA Hurricane Research Division Wind Analysis System (H*WIND) and the Interactive Objective Kinematic Analysis (IOKA) kinematic wind analyses, the Wave Model (WAM) offshore and Steady-State Irregular Wave (STWAVE) nearshore wind wave models, and the Advanced Circulation (ADCIRC) basin to channel-scale unstructured grid circulation model. The system emphasizes a high-resolution (down to 50 m) representation of the geometry, bathymetry, and topography; nonlinear coupling of all processes including wind wave radiation stress-induced set up; and objective specification of frictional parameters based on land-cover databases and commonly used parameters. Riverine flows and tides are validated for no storm conditions, while winds, wind waves, hydrographs, and high water marks are validated for Hurricanes Katrina and Rita.
