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Abstract
Daily data for the years 1932–75 are used in a study of the fluctuations in the arctic circulation over time scales of several days to several months. An updated set of normal sea level pressures is constructed, and a semiannual cycle is found in the high-latitude gradient of zonally averaged pressure. July is the only month in which a mean convergence of the low-level flow into the central arctic is indicated.
The high-latitude fields of sea level pressure, surface temperature and 700 mb height and temperature are represented in terms of empirical orthogonal functions in order to isolate the dominant modes of variability. The amplitudes of the functions are used to evaluate the daily persistence of arctic pressure anomalies as a function of season and to compare the persistence of arctic and midlatitude pressure anomalies. The month-to-month persistence of arctic pressure anomalies is found to be small, although the monthly persistence does exceed that expected from the lagged autocorrelations of the daily data.
Cross correlations between the anomaly fields of pressure (height) and temperature at the surface and 700 mb are evaluated at lags ranging from −8 to +8 months. The cross correlations differ substantially from zero only at 0 lag. Fluctuations in the first eigenvector of 700 mb temperature are in surprisingly good agreement with the surface temperature fluctuations reported in an earlier paper.
Abstract
Daily data for the years 1932–75 are used in a study of the fluctuations in the arctic circulation over time scales of several days to several months. An updated set of normal sea level pressures is constructed, and a semiannual cycle is found in the high-latitude gradient of zonally averaged pressure. July is the only month in which a mean convergence of the low-level flow into the central arctic is indicated.
The high-latitude fields of sea level pressure, surface temperature and 700 mb height and temperature are represented in terms of empirical orthogonal functions in order to isolate the dominant modes of variability. The amplitudes of the functions are used to evaluate the daily persistence of arctic pressure anomalies as a function of season and to compare the persistence of arctic and midlatitude pressure anomalies. The month-to-month persistence of arctic pressure anomalies is found to be small, although the monthly persistence does exceed that expected from the lagged autocorrelations of the daily data.
Cross correlations between the anomaly fields of pressure (height) and temperature at the surface and 700 mb are evaluated at lags ranging from −8 to +8 months. The cross correlations differ substantially from zero only at 0 lag. Fluctuations in the first eigenvector of 700 mb temperature are in surprisingly good agreement with the surface temperature fluctuations reported in an earlier paper.
Abstract
The linearized Boussinesq equations with rotation, viscosity, conduction, and a mean stratification are used to model the sea breeze in two dimensions. The motion is forced by a prescribed surface temperature function.
The linear model produces a sea breeze with realistic velocities and spatial dimensions. Hydrostatic solutions are found to differ very little from nonhydrostatic solutions. The only distinguishing feature of the solution at the inertial latitude is an amplitude maximum far from the coastline. Both the phase and the amplitude depend on the mean atmospheric stability. The computed vertical heat fluxes, when summed along the coastlines of the principal land masses, indicate that the sea breeze effect can account for several percent of the globally averaged vertical flux of sensible heat at a height of several hundred meters.
The land-sea temperature difference required by the model to create a net onshore flow in opposition to a basic current agrees well with the empirical criterion defined by Biggs and Graves.
The nonlinear advection process is studied with a finite-difference model based on a series of overlapping grids. The principal effect of the nonlinear terms is a landward advection oof the sea breeze circulation
Abstract
The linearized Boussinesq equations with rotation, viscosity, conduction, and a mean stratification are used to model the sea breeze in two dimensions. The motion is forced by a prescribed surface temperature function.
The linear model produces a sea breeze with realistic velocities and spatial dimensions. Hydrostatic solutions are found to differ very little from nonhydrostatic solutions. The only distinguishing feature of the solution at the inertial latitude is an amplitude maximum far from the coastline. Both the phase and the amplitude depend on the mean atmospheric stability. The computed vertical heat fluxes, when summed along the coastlines of the principal land masses, indicate that the sea breeze effect can account for several percent of the globally averaged vertical flux of sensible heat at a height of several hundred meters.
The land-sea temperature difference required by the model to create a net onshore flow in opposition to a basic current agrees well with the empirical criterion defined by Biggs and Graves.
The nonlinear advection process is studied with a finite-difference model based on a series of overlapping grids. The principal effect of the nonlinear terms is a landward advection oof the sea breeze circulation
Abstract
High-latitude monthly surface temperature data for the years 1954–75 are objectively analyzed. All existing monthly temperatures from drifting ice stations are included in the analyses. The variances about the monthly means are found to be no larger in the central Arctic than in the northern land areas. Surface temperature trends computed by linear regression vary considerably by season and by geographical region within the Arctic. The spatial distribution of the recent temperature trends is interpreted in terms of the empirical orthogonal functions accounting for the largest fractions of the temperature variance.
The net area-weighted 22-year trend for the region north of 60°N is −0.02°C year−1 but this relatively small value is found to be the resultant of cooling prior to the.mid-1960's and warming thereafter. During both the cooling and warming periods, the trends are found to be largest in the 70–80°N latitude belt. Inferences about the significance of the results are made by comparing the computed trends with those excepted when the temperatures are randomly distributed about their monthly means.
Abstract
High-latitude monthly surface temperature data for the years 1954–75 are objectively analyzed. All existing monthly temperatures from drifting ice stations are included in the analyses. The variances about the monthly means are found to be no larger in the central Arctic than in the northern land areas. Surface temperature trends computed by linear regression vary considerably by season and by geographical region within the Arctic. The spatial distribution of the recent temperature trends is interpreted in terms of the empirical orthogonal functions accounting for the largest fractions of the temperature variance.
The net area-weighted 22-year trend for the region north of 60°N is −0.02°C year−1 but this relatively small value is found to be the resultant of cooling prior to the.mid-1960's and warming thereafter. During both the cooling and warming periods, the trends are found to be largest in the 70–80°N latitude belt. Inferences about the significance of the results are made by comparing the computed trends with those excepted when the temperatures are randomly distributed about their monthly means.
Abstract
Twenty-five years (1958-82) of monthly 700 ml, geopotential forecasts produced by the U.S. National Weather Service are verified and then used in a series of temperature specification experiments. The forecasts show skill with respect to climatology through the positive correlations between forecast and observed anomalies in all calendar months. Improvement over persistence is apparent in the root mean square error, the mean absolute error, and the S skill score. The verification statistics also show a temporal trend toward smaller errors during the 1958-82 period.
Stepwise screening and EOF (empirical orthogonal function) regressions are compared as alternative strategies for the specification of surface station temperatures from 700 mb heights. When the statistical significance of the model order is comparable and the equations are applied to the developmental sample of 700 mb verification grids, the screening procedure outperforms the EOF procedure according to the mean absolute error, the fraction of described variance, and a 3-category skill score. However, when the same sets of equations are applied to an independent sample consisting of the most skillful 700 mb forecasts, the results of the screening procedure show considerably more degradation. Temperature forecasts derived fromthe two procedures have comparable 3-category skill scores, but the EOF-derived forecasts are characterized by smaller mean absolute errors and higher correlations between the forecast and observed temperatures. The tendency for less degradation of the EOF-derived forecasts is attributed to their smaller variances and to the ability of the EOFs to capture modest amounts of forecast skill regardless of the region in which the skill is achieved.
Abstract
Twenty-five years (1958-82) of monthly 700 ml, geopotential forecasts produced by the U.S. National Weather Service are verified and then used in a series of temperature specification experiments. The forecasts show skill with respect to climatology through the positive correlations between forecast and observed anomalies in all calendar months. Improvement over persistence is apparent in the root mean square error, the mean absolute error, and the S skill score. The verification statistics also show a temporal trend toward smaller errors during the 1958-82 period.
Stepwise screening and EOF (empirical orthogonal function) regressions are compared as alternative strategies for the specification of surface station temperatures from 700 mb heights. When the statistical significance of the model order is comparable and the equations are applied to the developmental sample of 700 mb verification grids, the screening procedure outperforms the EOF procedure according to the mean absolute error, the fraction of described variance, and a 3-category skill score. However, when the same sets of equations are applied to an independent sample consisting of the most skillful 700 mb forecasts, the results of the screening procedure show considerably more degradation. Temperature forecasts derived fromthe two procedures have comparable 3-category skill scores, but the EOF-derived forecasts are characterized by smaller mean absolute errors and higher correlations between the forecast and observed temperatures. The tendency for less degradation of the EOF-derived forecasts is attributed to their smaller variances and to the ability of the EOFs to capture modest amounts of forecast skill regardless of the region in which the skill is achieved.
Abstract
The use of a nested grid system in the numerical integration of a nonhydrostatic system of hydrodynamic equations is investigated. Computational problems introduced by the abandonment of the hydrostatic approximation are noted.
Tests in which a solitary inertial gravity wave is propagated through a periodic domain indicate that the computational noise due to the grid interaction is negligible when an upstream or a two-step Lax-Wendroff differencing scheme is used. A precipitating cumulus cloud is then simulated with several arrangements of grid points. The “nested” results differ very little from those of the corresponding “fine grid” simulation. Computational noise cannot be detected in the grid interaction zone even when this zone is in the active cloud area.
Abstract
The use of a nested grid system in the numerical integration of a nonhydrostatic system of hydrodynamic equations is investigated. Computational problems introduced by the abandonment of the hydrostatic approximation are noted.
Tests in which a solitary inertial gravity wave is propagated through a periodic domain indicate that the computational noise due to the grid interaction is negligible when an upstream or a two-step Lax-Wendroff differencing scheme is used. A precipitating cumulus cloud is then simulated with several arrangements of grid points. The “nested” results differ very little from those of the corresponding “fine grid” simulation. Computational noise cannot be detected in the grid interaction zone even when this zone is in the active cloud area.
Abstract
Several series of 30-day simulations with a global simulation model are used to evaluate the sensitivities to continental snow cover over North America and Eurasia. The model is initialized with National Meteorological Center analyses for specific dates during the winter of 1976/77 through 1983/84, and snow cover in each case is prescribed according to 1) the distribution derived from observational data; and 2) the distribution containing a corresponding anomaly of the opposite sign.
In ten pairs of midwinter forecasts, the major effect of extensive snow cover in eastern North America is a reduction of the near-surface air temperature in the vicinity of the snow anomaly. When snow cover is extensive, sea level pressures are somewhat lower and precipitation amounts somewhat higher offshore of the East Coast; sea level pressures are generally higher inland. In a set of six March cases, positive anomalies of Eurasian snow cover reduce the air temperatures by at least several degrees ceisius throughout the lower half of the troposphere in the region over and downstream of the snow anomaly. The positive Eurasian snow anomalies also produce systematically lower pressures and upper-air heights in the Aleutian region, higher pressures in the Asian Arctic, and lower pressures over western Europe and the extreme northeastern Atlantic. In the Eurasian experiments, the 30-day forecast pressures for the Eurasian hemisphere vary with snow coverage in a manner consistent with the observed pressure fields of the same months.
Abstract
Several series of 30-day simulations with a global simulation model are used to evaluate the sensitivities to continental snow cover over North America and Eurasia. The model is initialized with National Meteorological Center analyses for specific dates during the winter of 1976/77 through 1983/84, and snow cover in each case is prescribed according to 1) the distribution derived from observational data; and 2) the distribution containing a corresponding anomaly of the opposite sign.
In ten pairs of midwinter forecasts, the major effect of extensive snow cover in eastern North America is a reduction of the near-surface air temperature in the vicinity of the snow anomaly. When snow cover is extensive, sea level pressures are somewhat lower and precipitation amounts somewhat higher offshore of the East Coast; sea level pressures are generally higher inland. In a set of six March cases, positive anomalies of Eurasian snow cover reduce the air temperatures by at least several degrees ceisius throughout the lower half of the troposphere in the region over and downstream of the snow anomaly. The positive Eurasian snow anomalies also produce systematically lower pressures and upper-air heights in the Aleutian region, higher pressures in the Asian Arctic, and lower pressures over western Europe and the extreme northeastern Atlantic. In the Eurasian experiments, the 30-day forecast pressures for the Eurasian hemisphere vary with snow coverage in a manner consistent with the observed pressure fields of the same months.
Abstract
The sea ice simulations by the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) models for the climate of the twentieth century and for global warming scenarios have been synthesized. A large number of model simulations realistically captured the climatological annual mean, seasonal cycle, and temporal trends of sea ice area over the Northern Hemisphere during 1979–99, although there is considerable scatter among the models. In particular, multimodel ensemble means show promising estimates very close to observations for the late twentieth century. Model projections for the twenty-first century demonstrate the largest sea ice area decreases generally in the Special Report on Emission Scenarios (SRES) A1B and A2 scenarios compared with the B1 scenario, indicating large multimodel ensemble mean reductions of −3.54 ± 1.66 × 105 km2 decade−1 in A1B, −4.08 ± 1.33 × 105 km2 decade−1 in A2, and −2.22 ± 1.11 × 105 km2 decade−1 in B1. The corresponding percentage reductions are 31.1%, 33.4%, and 21.6% in the last 20 yr of the twenty-first century, relative to 1979–99. Furthermore, multiyear ice coverage decreases rapidly at rates of −3.86 ± 2.07 × 105 km2 decade−1 in A1B, −4.94 ± 1.91 × 105 km2 decade−1 in A2, and −2.67 ± 1.7107 × 105 km2 decade−1 in B1, making major contributions to the total ice reductions. In contrast, seasonal (first year) ice area increases by 1.10 ± 2.46 × 105 km2 decade−1, 1.99 ± 1.47 × 105 km2 decade−1, and 1.05 ± 1.9247 × 105 km2 decade−1 in the same scenarios, leading to decreases of 59.7%, 65.0%, and 45.8% of the multiyear ice area, and increases of 14.1%, 27.8%, and 11.2% of the seasonal ice area in the last 20 yr of this century. Statistical analysis shows that many of the models are consistent in the sea ice change projections among all scenarios. The results include an evaluation of the 99% confidence interval of the model-derived change of sea ice coverage, giving a quantification of uncertainties in estimating sea ice changes based on the participating models. Hence, the seasonal cycle of sea ice area is amplified and an increased large portion of seasonally ice-covered Arctic Ocean is expected at the end of the twenty-first century. The very different changes of multiyear and seasonal ice may have significant implications for the polar energy and hydrological budgets and pathways.
Abstract
The sea ice simulations by the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) models for the climate of the twentieth century and for global warming scenarios have been synthesized. A large number of model simulations realistically captured the climatological annual mean, seasonal cycle, and temporal trends of sea ice area over the Northern Hemisphere during 1979–99, although there is considerable scatter among the models. In particular, multimodel ensemble means show promising estimates very close to observations for the late twentieth century. Model projections for the twenty-first century demonstrate the largest sea ice area decreases generally in the Special Report on Emission Scenarios (SRES) A1B and A2 scenarios compared with the B1 scenario, indicating large multimodel ensemble mean reductions of −3.54 ± 1.66 × 105 km2 decade−1 in A1B, −4.08 ± 1.33 × 105 km2 decade−1 in A2, and −2.22 ± 1.11 × 105 km2 decade−1 in B1. The corresponding percentage reductions are 31.1%, 33.4%, and 21.6% in the last 20 yr of the twenty-first century, relative to 1979–99. Furthermore, multiyear ice coverage decreases rapidly at rates of −3.86 ± 2.07 × 105 km2 decade−1 in A1B, −4.94 ± 1.91 × 105 km2 decade−1 in A2, and −2.67 ± 1.7107 × 105 km2 decade−1 in B1, making major contributions to the total ice reductions. In contrast, seasonal (first year) ice area increases by 1.10 ± 2.46 × 105 km2 decade−1, 1.99 ± 1.47 × 105 km2 decade−1, and 1.05 ± 1.9247 × 105 km2 decade−1 in the same scenarios, leading to decreases of 59.7%, 65.0%, and 45.8% of the multiyear ice area, and increases of 14.1%, 27.8%, and 11.2% of the seasonal ice area in the last 20 yr of this century. Statistical analysis shows that many of the models are consistent in the sea ice change projections among all scenarios. The results include an evaluation of the 99% confidence interval of the model-derived change of sea ice coverage, giving a quantification of uncertainties in estimating sea ice changes based on the participating models. Hence, the seasonal cycle of sea ice area is amplified and an increased large portion of seasonally ice-covered Arctic Ocean is expected at the end of the twenty-first century. The very different changes of multiyear and seasonal ice may have significant implications for the polar energy and hydrological budgets and pathways.
Abstract
Daily observational data for thirty winters (1951–80) are used to test the hypothesis that anomalous distributions of snow and ice cover influence the intensification and/or trajectories of synoptic-scale cyclones. The pools of objectively chosen cases include 100 wintertime cyclonic events in the marginal snow/ice zones of each of three regions: eastern North America, the North Atlantic Ocean and the North Pacific Ocean. For each region, the errors of 24- and 48-hour force derived from a barotropic model, from persistence and from an objective analog procedure are stratified according to the concurrent anomalies of snow or ice cover. The results support the notion that the enhanced baroclinicity new the snow/ice margin contributes to stronger intensification and/or to motion parallel to the snow or ice margin in eastern North America and in the North Atlantic. A weaker signal is found in the North Pacific. The signal is qualitatively similar in the fields of 500 mb geopotential and sea level pressure, although the differences between the composites are statistically significant only in the sea level pressure fields. The results suggest that forecasts of weekly or monthly circulation patterns may, in situations of extreme snow/ice cover, be improved by consideration of observed snow/ice anomalies, if these anomalies persist through the forecast period.
Controlled experiments with the NCAR (National Center for Atmospheric Research) primitive equations forecast model show a weaker dependence on the extent of snow and ice, although qualitative similarities to the data-based results are detectable.
Abstract
Daily observational data for thirty winters (1951–80) are used to test the hypothesis that anomalous distributions of snow and ice cover influence the intensification and/or trajectories of synoptic-scale cyclones. The pools of objectively chosen cases include 100 wintertime cyclonic events in the marginal snow/ice zones of each of three regions: eastern North America, the North Atlantic Ocean and the North Pacific Ocean. For each region, the errors of 24- and 48-hour force derived from a barotropic model, from persistence and from an objective analog procedure are stratified according to the concurrent anomalies of snow or ice cover. The results support the notion that the enhanced baroclinicity new the snow/ice margin contributes to stronger intensification and/or to motion parallel to the snow or ice margin in eastern North America and in the North Atlantic. A weaker signal is found in the North Pacific. The signal is qualitatively similar in the fields of 500 mb geopotential and sea level pressure, although the differences between the composites are statistically significant only in the sea level pressure fields. The results suggest that forecasts of weekly or monthly circulation patterns may, in situations of extreme snow/ice cover, be improved by consideration of observed snow/ice anomalies, if these anomalies persist through the forecast period.
Controlled experiments with the NCAR (National Center for Atmospheric Research) primitive equations forecast model show a weaker dependence on the extent of snow and ice, although qualitative similarities to the data-based results are detectable.
Abstract
Monthly meteorological data for the years 1900–77 are used in an eigenvector analysis of the anomaly patterns of surface temperature, precipitation and sea level pressure over the United States. Approximately 70% of the variance is contained in the first three of 61 temperature eigenvectors and in the first three of 25 pressure eigenvectors. Large-scale patterns of precipitation are also identified, although the compression of the data is somewhat less effective. The first eigenvector of each variable contains anomalies of the same sign over most of the United States; the second and third modes describe gradients in approximately perpendicular directions.
Cross correlations between the amplitudes of eigenvectors of different variables are statistically significant, consistent with physical expectations, and, in some cases, are seasonally dependent. The first modes of both temperature and pressure are most persistent in the summer. Persistence on the seasonal time scale is generally largest for temperature and largest when summer is the antecedent season. The seasonal persistences of the amplitudes of the temperature eigenvectors are generally consistent with the persistences of station temperatures obtained recently by Namias (1978).
The most prominent feature of the frequency spectra is a strong peak at 2.1 years in the amplitude of the third temperature eigenvector.
Abstract
Monthly meteorological data for the years 1900–77 are used in an eigenvector analysis of the anomaly patterns of surface temperature, precipitation and sea level pressure over the United States. Approximately 70% of the variance is contained in the first three of 61 temperature eigenvectors and in the first three of 25 pressure eigenvectors. Large-scale patterns of precipitation are also identified, although the compression of the data is somewhat less effective. The first eigenvector of each variable contains anomalies of the same sign over most of the United States; the second and third modes describe gradients in approximately perpendicular directions.
Cross correlations between the amplitudes of eigenvectors of different variables are statistically significant, consistent with physical expectations, and, in some cases, are seasonally dependent. The first modes of both temperature and pressure are most persistent in the summer. Persistence on the seasonal time scale is generally largest for temperature and largest when summer is the antecedent season. The seasonal persistences of the amplitudes of the temperature eigenvectors are generally consistent with the persistences of station temperatures obtained recently by Namias (1978).
The most prominent feature of the frequency spectra is a strong peak at 2.1 years in the amplitude of the third temperature eigenvector.
Abstract
Satellite remote sensing data indicate that greenness has been increasing in the northern high latitudes, apparently in response to the warming of recent decades. To identify feedbacks of this land-cover change to the atmosphere, the authors employed the atmospheric general circulation model ARPEGE-CLIMAT, an adaptation of the Action de Recherche Petite Echelle Grande Echelle model for climate studies, to conduct a set of control and sensitivity modeling experiments. In the sensitivity experiments, they increased the greenness poleward of 60°N by 20% to mimic the manifestation of vegetation changes in the real world, and by 60% and 100% to represent potential aggressive vegetation change scenarios under global warming. In view of the direct exposure of vegetation to sunlight during the warm seasons, the authors focused their study on the results from late spring to early fall. The results revealed significant thermodynamic and hydrological impacts of the increased greenness in northern high latitudes, resulting in a warmer and wetter atmosphere. Surface and lower-tropospheric air temperature showed a marked increase, with a warming of 1°–2°C during much of the year when greenness is increased by 100%. Precipitation and evaporation also showed a notable increase of 10% during the summer. Snow cover decreased throughout the year, with a maximum reduction in the spring and early summer. The above changes are attributable to the following physical mechanisms: 1) increased net surface solar radiation due to a decreased surface albedo and enhanced snow–albedo feedback as a result of increased greenness; 2) intensified vegetative transpiration by the additional plant cover; and 3) reduced atmospheric stability leading to enhanced convective activity. The results imply that increased greenness is a potentially significant contributing factor to the amplified polar effects of global warming.
Abstract
Satellite remote sensing data indicate that greenness has been increasing in the northern high latitudes, apparently in response to the warming of recent decades. To identify feedbacks of this land-cover change to the atmosphere, the authors employed the atmospheric general circulation model ARPEGE-CLIMAT, an adaptation of the Action de Recherche Petite Echelle Grande Echelle model for climate studies, to conduct a set of control and sensitivity modeling experiments. In the sensitivity experiments, they increased the greenness poleward of 60°N by 20% to mimic the manifestation of vegetation changes in the real world, and by 60% and 100% to represent potential aggressive vegetation change scenarios under global warming. In view of the direct exposure of vegetation to sunlight during the warm seasons, the authors focused their study on the results from late spring to early fall. The results revealed significant thermodynamic and hydrological impacts of the increased greenness in northern high latitudes, resulting in a warmer and wetter atmosphere. Surface and lower-tropospheric air temperature showed a marked increase, with a warming of 1°–2°C during much of the year when greenness is increased by 100%. Precipitation and evaporation also showed a notable increase of 10% during the summer. Snow cover decreased throughout the year, with a maximum reduction in the spring and early summer. The above changes are attributable to the following physical mechanisms: 1) increased net surface solar radiation due to a decreased surface albedo and enhanced snow–albedo feedback as a result of increased greenness; 2) intensified vegetative transpiration by the additional plant cover; and 3) reduced atmospheric stability leading to enhanced convective activity. The results imply that increased greenness is a potentially significant contributing factor to the amplified polar effects of global warming.
