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Abstract
A new freezing-rain-days database was used to define the spatial and temporal distributions of freezing-rain days across the contiguous United States. The database contained 988 stations, spanning the period 1948–2000. Areas averaging one or more days of freezing rain annually included most of the eastern half of the United States and the Pacific Northwest. The national maximum is in portions of New York and Pennsylvania, a result of several weather conditions conducive to freezing rain. Other maxima included an east–west zone across the Midwest, an area along the eastern Appalachians, and the Pacific Northwest. The latter two maxima have high frequencies as a result of the mountains, which trap low-level cold air with warm air moving above, resulting in freezing rain. National maximum annual values during 1948–2000 were 3–5 times as great as annual averages, but the two patterns were similar. Average patterns for three discrete 17-yr periods between 1948 and 2000 were very similar, but the magnitudes of values differed greatly between periods. The earliest period, 1948–64, had many more freezing days than the latter periods. The high early values resulted in significant down trends for 1949–2000 in the Northwest, central, and Northeast regions. The 1965–76 period had the lowest frequency of freezing-rain days during 1949–2000. Months of first freezing-rain occurrences ranged from September to December, with November the predominant month in the eastern United States and October in the West. Months of last freezing events shifted latitudinally, with February being last along the Gulf of Mexico and April being last in the northern half of the United States. Nationally, peak months of freezing-rain days are December and January, and both have similar patterns. January averages are highest in the eastern half of the United States, and those in December are highest in the west. Freezing-rain days in these two months are more than one-half of those experienced each year in much of the United States.
Abstract
A new freezing-rain-days database was used to define the spatial and temporal distributions of freezing-rain days across the contiguous United States. The database contained 988 stations, spanning the period 1948–2000. Areas averaging one or more days of freezing rain annually included most of the eastern half of the United States and the Pacific Northwest. The national maximum is in portions of New York and Pennsylvania, a result of several weather conditions conducive to freezing rain. Other maxima included an east–west zone across the Midwest, an area along the eastern Appalachians, and the Pacific Northwest. The latter two maxima have high frequencies as a result of the mountains, which trap low-level cold air with warm air moving above, resulting in freezing rain. National maximum annual values during 1948–2000 were 3–5 times as great as annual averages, but the two patterns were similar. Average patterns for three discrete 17-yr periods between 1948 and 2000 were very similar, but the magnitudes of values differed greatly between periods. The earliest period, 1948–64, had many more freezing days than the latter periods. The high early values resulted in significant down trends for 1949–2000 in the Northwest, central, and Northeast regions. The 1965–76 period had the lowest frequency of freezing-rain days during 1949–2000. Months of first freezing-rain occurrences ranged from September to December, with November the predominant month in the eastern United States and October in the West. Months of last freezing events shifted latitudinally, with February being last along the Gulf of Mexico and April being last in the northern half of the United States. Nationally, peak months of freezing-rain days are December and January, and both have similar patterns. January averages are highest in the eastern half of the United States, and those in December are highest in the west. Freezing-rain days in these two months are more than one-half of those experienced each year in much of the United States.
Abstract
Time and space sampling is an increasingly critical aspect of Earth observation satellites. The highly eccentric orbit used by Soviet Molniya satellites functions much like a high-latitude geostationary orbit. Meteorological instruments placed on a satellite in a Molniya orbit would improve the temporal frequency of observation of high-latitude phenomena such as polar lows. Consideration of this new sampling strategy is suggested for future systems such as the “Earth Probe” satellites in the Mission to Planet Earth program as well as for operational meteorological satellite programs.
Abstract
Time and space sampling is an increasingly critical aspect of Earth observation satellites. The highly eccentric orbit used by Soviet Molniya satellites functions much like a high-latitude geostationary orbit. Meteorological instruments placed on a satellite in a Molniya orbit would improve the temporal frequency of observation of high-latitude phenomena such as polar lows. Consideration of this new sampling strategy is suggested for future systems such as the “Earth Probe” satellites in the Mission to Planet Earth program as well as for operational meteorological satellite programs.
Abstract
Upper tropospheric temperature anomalies are detected in brightness temperature data from the Nimbus 6 Scanning Microwave Spectrometer (SCAMS). Brightness temperature anomalies are related to surface pressure anomalies through the radiative transfer and hydrostatic equation. Surface wind speeds at outer radii are then estimated using the gradient wind equation and a shearing parameter. The method is first tested using simulated satellite data constructed from temperature, pressure and height data recorded by aircraft reconnaissance of four hurricanes. Wind speeds in the 80–95 kPa region are estimated with 2–3 m s−1 accuracy, Next, 55.45 GHz SCAMS data over eight typhoons during 1975 are used to estimate the radii of 15.4 m s−1 (30 kt) and 27.5 m a−1 (50 kt) winds. Accuracies of about ±80 and ±70 km, respectively, are found. It is suggested that the technique be further tested using data from the Microwave Sounding Unit (MSU) on board the TIROS-N and NOAA 6 satellites.
Abstract
Upper tropospheric temperature anomalies are detected in brightness temperature data from the Nimbus 6 Scanning Microwave Spectrometer (SCAMS). Brightness temperature anomalies are related to surface pressure anomalies through the radiative transfer and hydrostatic equation. Surface wind speeds at outer radii are then estimated using the gradient wind equation and a shearing parameter. The method is first tested using simulated satellite data constructed from temperature, pressure and height data recorded by aircraft reconnaissance of four hurricanes. Wind speeds in the 80–95 kPa region are estimated with 2–3 m s−1 accuracy, Next, 55.45 GHz SCAMS data over eight typhoons during 1975 are used to estimate the radii of 15.4 m s−1 (30 kt) and 27.5 m a−1 (50 kt) winds. Accuracies of about ±80 and ±70 km, respectively, are found. It is suggested that the technique be further tested using data from the Microwave Sounding Unit (MSU) on board the TIROS-N and NOAA 6 satellites.
Abstract
The passage of shallow cold fronts during the late spring and early summer months over the island of Taiwan is often accompanied by heavy rainfall and occasional flash flood episodes. Previous studies have emphasized the weak baroclinicity of these fronts and their possible modification by fluxes from the air-sea interface. In this study a cold frontal passage in the vicinity of Taiwan is analyzed using data gathered during the Taiwan Area Mesoscale Experiment (TAMEX) on 8 June 1987. At the northern extent of the TAMEX network the cold front was shallow (1–2 km deep) and moderately baroclinic with 5°-7°C temperature contrasts at the surface. A Doppler radar cross section of radial velocity reveals a structure similar to that of a density current at the leading edge of the shallow front. The postfrontal air man was substantially modified by oceanic heat fluxes as it moved southward over the warm ocean waters. This led to a 60%–70% decrease in the temperature contrast across the front between ocean stations at the northern and southern ends of the island, a distance of ∼400 km.
Frontal passages across Taiwan are also influenced by the presence of the Central Mountain Range (CMR), which has an average ridge elevation of ∼2500 m, and is oriented NNE-SSW along the major axis of the island. In the case described in this paper the CMR, 1) acts as a barrier to both the pre- and postfrontal flows, and 2) is influential by inducing thermally-driven diurnal circulations associated with differential heating of the sloped terrain and the nearby ocean. Terrain influences on the kinematics of the flow in the vicinity of the front are also shown to locally modify the frontal intensity.
The inhomogeneous distribution of precipitation attending the frontal passage is related to strong regional variations in thermodynamic stability across the island. These variations in stability are linked to the mesoscale effects of terrain, and to the larger-scale influence of advection of an unstable tropical air mass into the region by a low-level wind maximum.
Abstract
The passage of shallow cold fronts during the late spring and early summer months over the island of Taiwan is often accompanied by heavy rainfall and occasional flash flood episodes. Previous studies have emphasized the weak baroclinicity of these fronts and their possible modification by fluxes from the air-sea interface. In this study a cold frontal passage in the vicinity of Taiwan is analyzed using data gathered during the Taiwan Area Mesoscale Experiment (TAMEX) on 8 June 1987. At the northern extent of the TAMEX network the cold front was shallow (1–2 km deep) and moderately baroclinic with 5°-7°C temperature contrasts at the surface. A Doppler radar cross section of radial velocity reveals a structure similar to that of a density current at the leading edge of the shallow front. The postfrontal air man was substantially modified by oceanic heat fluxes as it moved southward over the warm ocean waters. This led to a 60%–70% decrease in the temperature contrast across the front between ocean stations at the northern and southern ends of the island, a distance of ∼400 km.
Frontal passages across Taiwan are also influenced by the presence of the Central Mountain Range (CMR), which has an average ridge elevation of ∼2500 m, and is oriented NNE-SSW along the major axis of the island. In the case described in this paper the CMR, 1) acts as a barrier to both the pre- and postfrontal flows, and 2) is influential by inducing thermally-driven diurnal circulations associated with differential heating of the sloped terrain and the nearby ocean. Terrain influences on the kinematics of the flow in the vicinity of the front are also shown to locally modify the frontal intensity.
The inhomogeneous distribution of precipitation attending the frontal passage is related to strong regional variations in thermodynamic stability across the island. These variations in stability are linked to the mesoscale effects of terrain, and to the larger-scale influence of advection of an unstable tropical air mass into the region by a low-level wind maximum.
Abstract
A technique is proposed for estimating tropical cyclone central pressure and surface wind speeds outside of the radius of maximum wind speed from the 55.45 GHz channel of the Scanning Microwave Spectrometer on board the Nimbus 6 satellite. The method was developed using measurements over eight typhoons and five hurricanes during 1975.
Abstract
A technique is proposed for estimating tropical cyclone central pressure and surface wind speeds outside of the radius of maximum wind speed from the 55.45 GHz channel of the Scanning Microwave Spectrometer on board the Nimbus 6 satellite. The method was developed using measurements over eight typhoons and five hurricanes during 1975.
Abstract
The characteristics of forecast-error covariances, which are of central interest in both data assimilation and ensemble forecasting, are poorly known. This paper considers the linear dynamics of these covariances and examines their evolution from (nearly) homogeneous and isotropic initial conditions in a turbulent quasigeostrophic flow qualitatively similar to that of the midlatitude troposphere. The experiments use ensembles of 100 solutions to estimate the error covariances. The error covariances evolve on a timescale of O(1 day), comparable to the advective timescale of the reference flow. This timescale also defines an initial period over which the errors develop characteristic features that are insensitive to the chosen initial statistics. These include 1) scales comparable to those of the reference flow, 2) potential vorticity (PV) concentrated where the gradient of the reference-flow PV is large, particularly at the surface and tropopause, and 3) little structure in the interior of the troposphere. In the error covariances, these characteristics are manifest as a strong spatial correlation between the PV variance and the magnitude of the reference-flow PV gradient and as a pronounced enhancement of the error correlations along reference-flow PV contours. The dynamical processes that result in such structure are also explored; the key is the advection of reference-flow PV by the error velocity, rather than the passive advection of the errors by the reference flow.
Abstract
The characteristics of forecast-error covariances, which are of central interest in both data assimilation and ensemble forecasting, are poorly known. This paper considers the linear dynamics of these covariances and examines their evolution from (nearly) homogeneous and isotropic initial conditions in a turbulent quasigeostrophic flow qualitatively similar to that of the midlatitude troposphere. The experiments use ensembles of 100 solutions to estimate the error covariances. The error covariances evolve on a timescale of O(1 day), comparable to the advective timescale of the reference flow. This timescale also defines an initial period over which the errors develop characteristic features that are insensitive to the chosen initial statistics. These include 1) scales comparable to those of the reference flow, 2) potential vorticity (PV) concentrated where the gradient of the reference-flow PV is large, particularly at the surface and tropopause, and 3) little structure in the interior of the troposphere. In the error covariances, these characteristics are manifest as a strong spatial correlation between the PV variance and the magnitude of the reference-flow PV gradient and as a pronounced enhancement of the error correlations along reference-flow PV contours. The dynamical processes that result in such structure are also explored; the key is the advection of reference-flow PV by the error velocity, rather than the passive advection of the errors by the reference flow.
Abstract
A climatological analysis of snowstorms across the contiguous United States, based on data from 1222 weather stations with data during 1901–2001, defined the spatial and temporal features. The average annual incidence of events creating 15.2 cm or more in 1 or 2 days, which are termed as snowstorms, exhibits great spatial variability. The pattern is latitudinal across most of the eastern half of the United States, averaging 0.1 storm (1 storm per 10 years) in the Deep South, increasing to 2 storms along the Canadian border. This pattern is interrupted by higher averages downwind of the Great Lakes and in the Appalachian Mountains. In the western third of the United States where snow falls, lower-elevation sites average 0.1–2 storms per year, but averages are much higher in the Cascade Range and Rocky Mountains, where 5–30 storms occur per year. Most areas of the United States have had years without snowstorms, but the annual minima are 1 or more storms in high-elevation areas of the West and Northeast. The pattern of annual maxima of storms is similar to the average pattern. The temporal distribution of snowstorms exhibited wide fluctuations during 1901–2000, with downward 100-yr trends in the lower Midwest, South, and West Coast. Upward trends occurred in the upper Midwest, East, and Northeast, and the national trend for 1901–2000 was upward, corresponding to trends in strong cyclonic activity. The peak periods of storm activity in the United States occurred during 1911–20 and 1971–80, and the lowest frequency was in 1931–40. Snowstorms first occur in September in the Rockies, in October in the high plains, in November across most of the United States, and in December in the Deep South. The month with the season’s last storms is December in the South and then shifts northward, with April the last month of snowstorms across most of the United States. Storms occur as late as May and June in the Rockies and Cascades. Snowstorms are most frequent in December downwind of the Great Lakes, with the peak of activity in January for most other areas of the United States.
Abstract
A climatological analysis of snowstorms across the contiguous United States, based on data from 1222 weather stations with data during 1901–2001, defined the spatial and temporal features. The average annual incidence of events creating 15.2 cm or more in 1 or 2 days, which are termed as snowstorms, exhibits great spatial variability. The pattern is latitudinal across most of the eastern half of the United States, averaging 0.1 storm (1 storm per 10 years) in the Deep South, increasing to 2 storms along the Canadian border. This pattern is interrupted by higher averages downwind of the Great Lakes and in the Appalachian Mountains. In the western third of the United States where snow falls, lower-elevation sites average 0.1–2 storms per year, but averages are much higher in the Cascade Range and Rocky Mountains, where 5–30 storms occur per year. Most areas of the United States have had years without snowstorms, but the annual minima are 1 or more storms in high-elevation areas of the West and Northeast. The pattern of annual maxima of storms is similar to the average pattern. The temporal distribution of snowstorms exhibited wide fluctuations during 1901–2000, with downward 100-yr trends in the lower Midwest, South, and West Coast. Upward trends occurred in the upper Midwest, East, and Northeast, and the national trend for 1901–2000 was upward, corresponding to trends in strong cyclonic activity. The peak periods of storm activity in the United States occurred during 1911–20 and 1971–80, and the lowest frequency was in 1931–40. Snowstorms first occur in September in the Rockies, in October in the high plains, in November across most of the United States, and in December in the Deep South. The month with the season’s last storms is December in the South and then shifts northward, with April the last month of snowstorms across most of the United States. Storms occur as late as May and June in the Rockies and Cascades. Snowstorms are most frequent in December downwind of the Great Lakes, with the peak of activity in January for most other areas of the United States.
Abstract
This paper presents the motivation for, and initial results from, the Multiple Altimeter Beam Experimental lidar (MABEL) instrument. The MABEL instrument provides a new capability for airborne altimetry measurements and serves as a prototype and simulator for the upcoming NASA second-generation Ice, Cloud, and Land Elevation Satellite (ICESat-2) mission. Designed to be highly flexible in measurement capability, MABEL serves as both a demonstration of measurement capability and a science tool for cryospheric and biospheric remote sensing. It is important to document the instrument specifications and essential background information to provide a suitable reference for the detailed MABEL results and science investigation publications that will be forthcoming.
Abstract
This paper presents the motivation for, and initial results from, the Multiple Altimeter Beam Experimental lidar (MABEL) instrument. The MABEL instrument provides a new capability for airborne altimetry measurements and serves as a prototype and simulator for the upcoming NASA second-generation Ice, Cloud, and Land Elevation Satellite (ICESat-2) mission. Designed to be highly flexible in measurement capability, MABEL serves as both a demonstration of measurement capability and a science tool for cryospheric and biospheric remote sensing. It is important to document the instrument specifications and essential background information to provide a suitable reference for the detailed MABEL results and science investigation publications that will be forthcoming.
Abstract
Experimental ensemble predictions of tropical cyclone (TC) tracks from the ensemble Kalman filter (EnKF) using the Global Forecast System (GFS) model were recently validated for the 2009 Northern Hemisphere hurricane season by Hamill et al. A similar suite of tests is described here for the 2010 season. Two major changes were made this season: 1) a reduction in the resolution of the GFS model, from 2009’s T384L64 (~31 km at 25°N) to 2010’s T254L64 (~47 km at 25°N), and some changes in model physics; and 2) the addition of a limited test of deterministic forecasts initialized from a hybrid three-dimensional variational data assimilation (3D-Var)/EnKF method.
The GFS/EnKF ensembles continued to produce reduced track errors relative to operational ensemble forecasts created by the National Centers for Environmental Prediction (NCEP), the Met Office (UKMO), and the Canadian Meteorological Centre (CMC). The GFS/EnKF was not uniformly as skillful as the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system. GFS/EnKF track forecasts had slightly higher error than ECMWF at longer leads, especially in the western North Pacific, and exhibited poorer calibration between spread and error than in 2009, perhaps in part because of lower model resolution. Deterministic forecasts from the hybrid were competitive with deterministic EnKF ensemble-mean forecasts and superior in track error to those initialized from the operational variational algorithm, the Gridpoint Statistical Interpolation (GSI). Pending further successful testing, the National Oceanic and Atmospheric Administration (NOAA) intends to implement the global hybrid system operationally for data assimilation.
Abstract
Experimental ensemble predictions of tropical cyclone (TC) tracks from the ensemble Kalman filter (EnKF) using the Global Forecast System (GFS) model were recently validated for the 2009 Northern Hemisphere hurricane season by Hamill et al. A similar suite of tests is described here for the 2010 season. Two major changes were made this season: 1) a reduction in the resolution of the GFS model, from 2009’s T384L64 (~31 km at 25°N) to 2010’s T254L64 (~47 km at 25°N), and some changes in model physics; and 2) the addition of a limited test of deterministic forecasts initialized from a hybrid three-dimensional variational data assimilation (3D-Var)/EnKF method.
The GFS/EnKF ensembles continued to produce reduced track errors relative to operational ensemble forecasts created by the National Centers for Environmental Prediction (NCEP), the Met Office (UKMO), and the Canadian Meteorological Centre (CMC). The GFS/EnKF was not uniformly as skillful as the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system. GFS/EnKF track forecasts had slightly higher error than ECMWF at longer leads, especially in the western North Pacific, and exhibited poorer calibration between spread and error than in 2009, perhaps in part because of lower model resolution. Deterministic forecasts from the hybrid were competitive with deterministic EnKF ensemble-mean forecasts and superior in track error to those initialized from the operational variational algorithm, the Gridpoint Statistical Interpolation (GSI). Pending further successful testing, the National Oceanic and Atmospheric Administration (NOAA) intends to implement the global hybrid system operationally for data assimilation.
Abstract
The next-generation U.S. polar-orbiting environmental satellite program, the Joint Polar Satellite System (JPSS), promises unprecedented capabilities for nighttime remote sensing by way of the day/night band (DNB) low-light visible sensor. The DNB will use moonlight illumination to characterize properties of the atmosphere and surface that conventionally have been limited to daytime observations. Since the moon is a highly variable source of visible light, an important question is where and when various levels of lunar illumination will be available. Here, nighttime moonlight availability was examined based on simulations done in the context of Visible/Infrared Imager Radiometer Suite (VIIRS)/DNB coverage and sensitivity. Results indicate that roughly 45% of all JPSS-orbit [sun-synchronous, 1330 local equatorial crossing time on the ascending node (LTAN)] nighttime observations in the tropics and midlatitudes would provide levels of moonlight at crescent moon or greater. Two other orbits, 1730 and 2130 LTAN, were also considered. The inclusion of a 2130 LTAN satellite would provide similar availability to 1330 LTAN in terms of total moonlit nights, but with approximately a third of those nights being additional because of this orbit’s capture of a different portion of the lunar cycle. Nighttime availability is highly variable for near-terminator orbits. A 1-h shift from the 1730 LTAN near-terminator orbit to 1630 LTAN would nearly double the nighttime availability globally from this orbit, including expanded availability at midlatitudes. In contrast, a later shift to 1830 LTAN has a negligible effect. The results are intended to provide high-level guidance for mission planners, algorithm developers, and various users of low-light applications from these future satellite programs.
Abstract
The next-generation U.S. polar-orbiting environmental satellite program, the Joint Polar Satellite System (JPSS), promises unprecedented capabilities for nighttime remote sensing by way of the day/night band (DNB) low-light visible sensor. The DNB will use moonlight illumination to characterize properties of the atmosphere and surface that conventionally have been limited to daytime observations. Since the moon is a highly variable source of visible light, an important question is where and when various levels of lunar illumination will be available. Here, nighttime moonlight availability was examined based on simulations done in the context of Visible/Infrared Imager Radiometer Suite (VIIRS)/DNB coverage and sensitivity. Results indicate that roughly 45% of all JPSS-orbit [sun-synchronous, 1330 local equatorial crossing time on the ascending node (LTAN)] nighttime observations in the tropics and midlatitudes would provide levels of moonlight at crescent moon or greater. Two other orbits, 1730 and 2130 LTAN, were also considered. The inclusion of a 2130 LTAN satellite would provide similar availability to 1330 LTAN in terms of total moonlit nights, but with approximately a third of those nights being additional because of this orbit’s capture of a different portion of the lunar cycle. Nighttime availability is highly variable for near-terminator orbits. A 1-h shift from the 1730 LTAN near-terminator orbit to 1630 LTAN would nearly double the nighttime availability globally from this orbit, including expanded availability at midlatitudes. In contrast, a later shift to 1830 LTAN has a negligible effect. The results are intended to provide high-level guidance for mission planners, algorithm developers, and various users of low-light applications from these future satellite programs.
