Search Results
You are looking at 1 - 9 of 9 items for :
- Author or Editor: R. G. Barry x
- Article x
- Refine by Access: Content accessible to me x
Abstract
The statistical relationships between lake freeze-up/lake ice break-up dates and air temperature means over various time periods are analyzed for 63 lakes in Finland. Mean temperatures for the individual months before the lake event dates are strongly correlated with these dates; significant correlations hold for periods up to five months in length before freeze-up. Regression coefficients depend on location, but are consistent within regions. Latitude and distance from the coast are the most important sources of variation in the regression coefficients.
The regression coefficients are used to translate changes in lake freeze-up/break-up dates into estimated changes in air temperature. In southern Finland a five day change in freeze-up date would represent a 1.1°C change in November temperature of the same sign. A time series of November temperatures estimated from lake freeze-up dates is derived and compared with observations at Helsinki. The spatial pattern of temperature change over time is also examined using the freeze-up dates. Freeze-up/break-up dates provide a useful proxy for air temperature estimates in data-sparse regions of middle-high latitudes and could permit rapid satellite monitoring of climate perturbations.
Abstract
The statistical relationships between lake freeze-up/lake ice break-up dates and air temperature means over various time periods are analyzed for 63 lakes in Finland. Mean temperatures for the individual months before the lake event dates are strongly correlated with these dates; significant correlations hold for periods up to five months in length before freeze-up. Regression coefficients depend on location, but are consistent within regions. Latitude and distance from the coast are the most important sources of variation in the regression coefficients.
The regression coefficients are used to translate changes in lake freeze-up/break-up dates into estimated changes in air temperature. In southern Finland a five day change in freeze-up date would represent a 1.1°C change in November temperature of the same sign. A time series of November temperatures estimated from lake freeze-up dates is derived and compared with observations at Helsinki. The spatial pattern of temperature change over time is also examined using the freeze-up dates. Freeze-up/break-up dates provide a useful proxy for air temperature estimates in data-sparse regions of middle-high latitudes and could permit rapid satellite monitoring of climate perturbations.
Abstract
The TAXIR information retrieval system, originally developed for taxonomic research, is described in the context of its application to climatological data. Data banks for four mountain stations in Colorado have been established and analysed using TAXIR and a package of statistical routines. The procedures and their cost effectiveness are evaluated.
Abstract
The TAXIR information retrieval system, originally developed for taxonomic research, is described in the context of its application to climatological data. Data banks for four mountain stations in Colorado have been established and analysed using TAXIR and a package of statistical routines. The procedures and their cost effectiveness are evaluated.
Abstract
The NCAR global circulation model has been used to simulate global atmospheric conditions using boundary conditions representing those of the present day and those of the Würm/Wisconsin glacial maximum at about 20,000 years ago, for January and July cases.
The mean zonal wind strength in the July ice age case in the middle latitudes of the Northern Hemisphere was comparable with present winter conditions. Also in the ice age cases, the upper westerlies were not apparently displaced south of the Laurentide ice sheet. The Icelandic and Aleutian lows in January were displaced 10° southward, the Siberian high remained unchanged from the control situation, and a new low center was found over eastern Europe and the European USSR. In July high pressure developed over most of Asia. Maps of cyclone frequency in a 30-day period showed the influence of major ice sheets and sea ice in displacing zones of cyclone activity southward in January. Frequent cyclones occurred over central North America and there was a continuation of cyclone activity in the North Atlantic and from eastern Europe into Asia. There was virtually no cyclonic activity near the Laurentide ice sheet in July.
Cloud cover and precipitation were also analyzed. Changes in precipitation for the glacial maximum cases are mainly quantitative rather than affecting its spatial distribution. The zonal averages show small changes for the Southern Hemisphere. In the Northern Hemisphere precipitation was decreased slightly in winter with most pronounced effects between 0–10N and 55–70N. The summer shows a dramatic reduction of precipitation north of 10N.
There is broad agreement between these paleo-climatological reconstructions and those of other studies using different models.
Abstract
The NCAR global circulation model has been used to simulate global atmospheric conditions using boundary conditions representing those of the present day and those of the Würm/Wisconsin glacial maximum at about 20,000 years ago, for January and July cases.
The mean zonal wind strength in the July ice age case in the middle latitudes of the Northern Hemisphere was comparable with present winter conditions. Also in the ice age cases, the upper westerlies were not apparently displaced south of the Laurentide ice sheet. The Icelandic and Aleutian lows in January were displaced 10° southward, the Siberian high remained unchanged from the control situation, and a new low center was found over eastern Europe and the European USSR. In July high pressure developed over most of Asia. Maps of cyclone frequency in a 30-day period showed the influence of major ice sheets and sea ice in displacing zones of cyclone activity southward in January. Frequent cyclones occurred over central North America and there was a continuation of cyclone activity in the North Atlantic and from eastern Europe into Asia. There was virtually no cyclonic activity near the Laurentide ice sheet in July.
Cloud cover and precipitation were also analyzed. Changes in precipitation for the glacial maximum cases are mainly quantitative rather than affecting its spatial distribution. The zonal averages show small changes for the Southern Hemisphere. In the Northern Hemisphere precipitation was decreased slightly in winter with most pronounced effects between 0–10N and 55–70N. The summer shows a dramatic reduction of precipitation north of 10N.
There is broad agreement between these paleo-climatological reconstructions and those of other studies using different models.
Abstract
The variation over uneven terrain of the daily total of incident shortwave (global) radiation under cloudless conditions may be estimated by existing methods for calculating direct and diffuse solar radiation on a slope. A computer program for performing these calculations, incorporating a technique to determine when the direct rays of the sun are screened by the horizon at each point, is described. The adequacy of the approximation for diffuse radiation is considered by comparison with published data. Computations for an area of east Baffin Island, Northwest Territories, Canada, demonstrate that the occurrence of glaciers there is influenced both by elevation and by solar radiation. The potential of such computations as an aid in selecting station sites for climatological studies is also discussed.
Abstract
The variation over uneven terrain of the daily total of incident shortwave (global) radiation under cloudless conditions may be estimated by existing methods for calculating direct and diffuse solar radiation on a slope. A computer program for performing these calculations, incorporating a technique to determine when the direct rays of the sun are screened by the horizon at each point, is described. The adequacy of the approximation for diffuse radiation is considered by comparison with published data. Computations for an area of east Baffin Island, Northwest Territories, Canada, demonstrate that the occurrence of glaciers there is influenced both by elevation and by solar radiation. The potential of such computations as an aid in selecting station sites for climatological studies is also discussed.
Abstract
As part of an investigation into terminal airspace productivity sponsored by the NASA Ames Research Center, a study was performed at the Forecast Systems Laboratory to investigate sources of wind forecast error and to assess differences in wind forecast accuracy between the 60-km Rapid Update Cycle, version 1 (RUC-1), and the newer 40-km RUC-2. Improved knowledge of these errors is important for development of air traffic management automation tools under development at NASA Ames and elsewhere. This information is also useful for operational users of RUC forecast winds. To perform this study, commercial aircraft reports of wind reported through Aircraft Communications, Addressing, and Reporting System (ACARS) were collected in a region over the western and central United States for a 13-month period, along with RUC-1 and RUC-2 wind forecasts. Differences between forecasts and ACARS observations and estimates of ACARS wind observation error itself were both calculated.
It was found that rms vector differences between observations and forecasts from either version of the RUC increased as wind speed increased, and also as altitude increased and in winter months (both associated with higher wind speed). Wind errors increased when thunderstorms were nearby and were smaller in wintertime precipitation situations. The study also showed that considerable progress has been made in the accuracy of wind forecasts to be used for air traffic management by the introduction of the RUC-2 system, replacing the previous RUC-1 system. Improvement was made both in the intrinsic accuracy as well as in the time availability, both contributing to the overall improvement in the actual wind forecast available for air traffic management purposes. Using 3-h forecasts, RUC-2 demonstrated a reduction in mean daily rms vectors of approximately 10% over that for RUC-1 based on accuracy improvements alone. This error reduction increased to about 22% when time availability improvements were added. It was also found that the degree of improvement from the RUC-2 increased substantially for periods with a large number of significant wind errors. The percentage of individual vector errors greater than 10 m s−1 was reduced by RUC-2 from 8% (RUC-1) to 3% overall and from 17% to 7% during the worst month. Such peak error periods have a strong impact on air traffic management automation tools. Last, it was found that the estimated trajectory projection errors from the RUC-2 using 1–2-h forecasts averaged 9 s for ascent/descent flight segments of approximately 15 min, and about 10 s for en route segments of the same duration.
Abstract
As part of an investigation into terminal airspace productivity sponsored by the NASA Ames Research Center, a study was performed at the Forecast Systems Laboratory to investigate sources of wind forecast error and to assess differences in wind forecast accuracy between the 60-km Rapid Update Cycle, version 1 (RUC-1), and the newer 40-km RUC-2. Improved knowledge of these errors is important for development of air traffic management automation tools under development at NASA Ames and elsewhere. This information is also useful for operational users of RUC forecast winds. To perform this study, commercial aircraft reports of wind reported through Aircraft Communications, Addressing, and Reporting System (ACARS) were collected in a region over the western and central United States for a 13-month period, along with RUC-1 and RUC-2 wind forecasts. Differences between forecasts and ACARS observations and estimates of ACARS wind observation error itself were both calculated.
It was found that rms vector differences between observations and forecasts from either version of the RUC increased as wind speed increased, and also as altitude increased and in winter months (both associated with higher wind speed). Wind errors increased when thunderstorms were nearby and were smaller in wintertime precipitation situations. The study also showed that considerable progress has been made in the accuracy of wind forecasts to be used for air traffic management by the introduction of the RUC-2 system, replacing the previous RUC-1 system. Improvement was made both in the intrinsic accuracy as well as in the time availability, both contributing to the overall improvement in the actual wind forecast available for air traffic management purposes. Using 3-h forecasts, RUC-2 demonstrated a reduction in mean daily rms vectors of approximately 10% over that for RUC-1 based on accuracy improvements alone. This error reduction increased to about 22% when time availability improvements were added. It was also found that the degree of improvement from the RUC-2 increased substantially for periods with a large number of significant wind errors. The percentage of individual vector errors greater than 10 m s−1 was reduced by RUC-2 from 8% (RUC-1) to 3% overall and from 17% to 7% during the worst month. Such peak error periods have a strong impact on air traffic management automation tools. Last, it was found that the estimated trajectory projection errors from the RUC-2 using 1–2-h forecasts averaged 9 s for ascent/descent flight segments of approximately 15 min, and about 10 s for en route segments of the same duration.
Abstract
Previous work has considered tornado occurrence with respect to radar data, both WSR-88D and mobile research radars, and a few studies have examined techniques to potentially improve tornado warning performance. To date, though, there has been little work focusing on systematic, large-sample evaluation of National Weather Service (NWS) tornado warnings with respect to radar-observable quantities and the near-storm environment. In this work, three full years (2016–18) of NWS tornado warnings across the contiguous United States were examined, in conjunction with supporting data in the few minutes preceding warning issuance, or tornado formation in the case of missed events. The investigation herein examines WSR-88D and Storm Prediction Center (SPC) mesoanalysis data associated with these tornado warnings with comparisons made to the current Warning Decision Training Division (WDTD) guidance. Combining low-level rotational velocity and the significant tornado parameter (STP), as used in prior work, shows promise as a means to estimate tornado warning performance, as well as relative changes in performance as criteria thresholds vary. For example, low-level rotational velocity peaking in excess of 30 kt (15 m s−1), in a near-storm environment, which is not prohibitive for tornadoes (STP > 0), results in an increased probability of detection and reduced false alarms compared to observed NWS tornado warning metrics. Tornado warning false alarms can also be reduced through limiting warnings with weak (<30 kt), broad (>1 n mi; 1 n mi = 1.852 km) circulations in a poor (STP = 0) environment, careful elimination of velocity data artifacts like sidelobe contamination, and through greater scrutiny of human-based tornado reports in otherwise questionable scenarios.
Abstract
Previous work has considered tornado occurrence with respect to radar data, both WSR-88D and mobile research radars, and a few studies have examined techniques to potentially improve tornado warning performance. To date, though, there has been little work focusing on systematic, large-sample evaluation of National Weather Service (NWS) tornado warnings with respect to radar-observable quantities and the near-storm environment. In this work, three full years (2016–18) of NWS tornado warnings across the contiguous United States were examined, in conjunction with supporting data in the few minutes preceding warning issuance, or tornado formation in the case of missed events. The investigation herein examines WSR-88D and Storm Prediction Center (SPC) mesoanalysis data associated with these tornado warnings with comparisons made to the current Warning Decision Training Division (WDTD) guidance. Combining low-level rotational velocity and the significant tornado parameter (STP), as used in prior work, shows promise as a means to estimate tornado warning performance, as well as relative changes in performance as criteria thresholds vary. For example, low-level rotational velocity peaking in excess of 30 kt (15 m s−1), in a near-storm environment, which is not prohibitive for tornadoes (STP > 0), results in an increased probability of detection and reduced false alarms compared to observed NWS tornado warning metrics. Tornado warning false alarms can also be reduced through limiting warnings with weak (<30 kt), broad (>1 n mi; 1 n mi = 1.852 km) circulations in a poor (STP = 0) environment, careful elimination of velocity data artifacts like sidelobe contamination, and through greater scrutiny of human-based tornado reports in otherwise questionable scenarios.
Abstract
An assessment is presented on the relative forecast impact on the performance of a numerical weather prediction model from eight different observation data types: aircraft, profiler, radiosonde, velocity azimuth display (VAD), GPS-derived precipitable water, aviation routine weather report (METAR; surface), surface mesonet, and satellite-based atmospheric motion vectors. A series of observation sensitivity experiments was conducted using the Rapid Update Cycle (RUC) model/assimilation system in which various data sources were denied to assess the relative importance of the different data types for short-range (3–12 h) wind, temperature, and relative humidity forecasts at different vertical levels and near the surface. These experiments were conducted for two 10-day periods, one in November–December 2006 and one in August 2007. These experiments show positive short-range forecast impacts from most of the contributors to the heterogeneous observing system over the RUC domain. In particular, aircraft observations had the largest overall impact for forecasts initialized 3–6 h before 0000 or 1200 UTC, considered over the full depth (1000–100 hPa), followed by radiosonde observations, even though the latter are available only every 12 h. Profiler data (including at a hypothetical 8-km depth), GPS-precipitable water estimates, and surface observations also led to significant improvements in short-range forecast skill.
Abstract
An assessment is presented on the relative forecast impact on the performance of a numerical weather prediction model from eight different observation data types: aircraft, profiler, radiosonde, velocity azimuth display (VAD), GPS-derived precipitable water, aviation routine weather report (METAR; surface), surface mesonet, and satellite-based atmospheric motion vectors. A series of observation sensitivity experiments was conducted using the Rapid Update Cycle (RUC) model/assimilation system in which various data sources were denied to assess the relative importance of the different data types for short-range (3–12 h) wind, temperature, and relative humidity forecasts at different vertical levels and near the surface. These experiments were conducted for two 10-day periods, one in November–December 2006 and one in August 2007. These experiments show positive short-range forecast impacts from most of the contributors to the heterogeneous observing system over the RUC domain. In particular, aircraft observations had the largest overall impact for forecasts initialized 3–6 h before 0000 or 1200 UTC, considered over the full depth (1000–100 hPa), followed by radiosonde observations, even though the latter are available only every 12 h. Profiler data (including at a hypothetical 8-km depth), GPS-precipitable water estimates, and surface observations also led to significant improvements in short-range forecast skill.
Abstract
Prediction of ice formation in clouds presents one of the grand challenges in the atmospheric sciences. Immersion freezing initiated by ice-nucleating particles (INPs) is the dominant pathway of primary ice crystal formation in mixed-phase clouds, where supercooled water droplets and ice crystals coexist, with important implications for the hydrological cycle and climate. However, derivation of INP number concentrations from an ambient aerosol population in cloud-resolving and climate models remains highly uncertain. We conducted an aerosol–ice formation closure pilot study using a field-observational approach to evaluate the predictive capability of immersion freezing INPs. The closure study relies on collocated measurements of the ambient size-resolved and single-particle composition and INP number concentrations. The acquired particle data serve as input in several immersion freezing parameterizations, which are employed in cloud-resolving and climate models, for prediction of INP number concentrations. We discuss in detail one closure case study in which a front passed through the measurement site, resulting in a change of ambient particle and INP populations. We achieved closure in some circumstances within uncertainties, but we emphasize the need for freezing parameterization of potentially missing INP types and evaluation of the choice of parameterization to be employed. Overall, this closure pilot study aims to assess the level of parameter details and measurement strategies needed to achieve aerosol–ice formation closure. The closure approach is designed to accurately guide immersion freezing schemes in models, and ultimately identify the leading causes for climate model bias in INP predictions.
Abstract
Prediction of ice formation in clouds presents one of the grand challenges in the atmospheric sciences. Immersion freezing initiated by ice-nucleating particles (INPs) is the dominant pathway of primary ice crystal formation in mixed-phase clouds, where supercooled water droplets and ice crystals coexist, with important implications for the hydrological cycle and climate. However, derivation of INP number concentrations from an ambient aerosol population in cloud-resolving and climate models remains highly uncertain. We conducted an aerosol–ice formation closure pilot study using a field-observational approach to evaluate the predictive capability of immersion freezing INPs. The closure study relies on collocated measurements of the ambient size-resolved and single-particle composition and INP number concentrations. The acquired particle data serve as input in several immersion freezing parameterizations, which are employed in cloud-resolving and climate models, for prediction of INP number concentrations. We discuss in detail one closure case study in which a front passed through the measurement site, resulting in a change of ambient particle and INP populations. We achieved closure in some circumstances within uncertainties, but we emphasize the need for freezing parameterization of potentially missing INP types and evaluation of the choice of parameterization to be employed. Overall, this closure pilot study aims to assess the level of parameter details and measurement strategies needed to achieve aerosol–ice formation closure. The closure approach is designed to accurately guide immersion freezing schemes in models, and ultimately identify the leading causes for climate model bias in INP predictions.
Abstract
International Arctic Systems for Observing the Atmosphere (IASOA) activities and partnerships were initiated as a part of the 2007–09 International Polar Year (IPY) and are expected to continue for many decades as a legacy program. The IASOA focus is on coordinating intensive measurements of the Arctic atmosphere collected in the United States, Canada, Russia, Norway, Finland, and Greenland to create synthesis science that leads to an understanding of why and not just how the Arctic atmosphere is evolving. The IASOA premise is that there are limitations with Arctic modeling and satellite observations that can only be addressed with boots-on-the-ground, in situ observations and that the potential of combining individual station and network measurements into an integrated observing system is tremendous. The IASOA vision is that by further integrating with other network observing programs focusing on hydrology, glaciology, oceanography, terrestrial, and biological systems it will be possible to understand the mechanisms of the entire Arctic system, perhaps well enough for humans to mitigate undesirable variations and adapt to inevitable change.
Abstract
International Arctic Systems for Observing the Atmosphere (IASOA) activities and partnerships were initiated as a part of the 2007–09 International Polar Year (IPY) and are expected to continue for many decades as a legacy program. The IASOA focus is on coordinating intensive measurements of the Arctic atmosphere collected in the United States, Canada, Russia, Norway, Finland, and Greenland to create synthesis science that leads to an understanding of why and not just how the Arctic atmosphere is evolving. The IASOA premise is that there are limitations with Arctic modeling and satellite observations that can only be addressed with boots-on-the-ground, in situ observations and that the potential of combining individual station and network measurements into an integrated observing system is tremendous. The IASOA vision is that by further integrating with other network observing programs focusing on hydrology, glaciology, oceanography, terrestrial, and biological systems it will be possible to understand the mechanisms of the entire Arctic system, perhaps well enough for humans to mitigate undesirable variations and adapt to inevitable change.
