Various global empirical wind models play an important role in our understanding of main regularities in the upper mesosphere/lower thermosphere dynamics. Among others, the models derived from the ground-based radar wind mea- surements have been published by Portnyagin (1984, 1987), Portnyagin and Solovjova (1992). Constant accumulation of data sets collected from ground- and space-based instruments has continuously stimulated the development and improve- ment of these models. The updated version of the models (hereafter called as GEWM) is based on the most recently available ground-based meteor radar and MF (partial reflec- tion) wind measurements. Meanwhile, direct wind observa- tions from UARS experiment provide unique global data sets with a substantial increase in the quantity of available wind measurements in the mesosphere and lower thermosphere. Based on the WINDII green line wind data, Wang et al. (1997) have proposed an empirical horizontal wind model. Here we present the results of comparison between zonal winds retrieved from the GEWM and the WINDII model to show their general consistency and significant difference.
QBO in zonal wind in the lower stratosphere (30 hPa) and the percentage of departure of the summer monsoon rainfall of India. They found that strong easterly phase of the QBO was associated with weak Indian monsoon and weak easterly/westerly phase with strong monsoon. They found that 15% of variability in the summer mon- soon rainfall over India is associated with the phase of the QBO. The inter-annual variability of the Indian sum- mer monsoon (June-September) rainfall correlated with the zonal winds at 10 hPa (30 km) and 30 hPa (24 km) at Balboa station for the 28-year period (1958-85) concluded that the variations in the zonal wind anomalies at 10 hPa are highly correlated to the monsoon rainfall. And it was found that zonal wind anomalies at 10 hPa (30 km) lead those at 30 hPa (24 km) by 6 months, providing a longer lead-time for predicting the Indian monsoon rainfall . Several studies in the past established the link between the stratospheric zonal wind and Indian summer monsoon -. The composite of mean tropopause height for excess and deficient monsoon years showed that all India mean tropopause height is statistically higher in excess monsoon years than the deficient monsoon years . Rajeevan has studied the upper tropospheric circulation and thermal anomalies over the central Asia associated with major drought and floods in India using the upper air data of 21 stations for 22 years (1961-1982) . From their analysis it is observed that significant differences occur between the anoma- lies during the drought and flood years. Monthly zonal mean wind anomaly for 10 hPa, 30 hPa, and 50 hPa at Balboa an equatorial station (9 ˚N, 80˚W) correlated with the summer rainfall of India for a 29-year period got a correlation of 0.57 . In this paper an attempt has been made to understand the stratospheric and troposphere zonal wind variation with Indian Summer Monsoon Rainfall variability.
12 Read more
In idealized theory, the subtropical jets form at the edges of the poleward-moving upper tropospheric branches of the Hadley circulation in each hemisphere (e.g., Schneider, 2006). This motivates the use of the latitude of the sub- tropical jet as an indicator of the tropical width. However, upper-level winds are also strongly affected by midlatitude macroturbulence and stratospheric processes, obliging cau- tion in associating the latitude of maximal zonal wind with the above conceptual picture of the latitude of the subtropical jet. Indeed, recent studies find that STJ-based metrics of the tropical width are weakly correlated with lower-troposphere metrics (Solomon et al., 2016; Davis and Birner, 2017). Common STJ-based metrics take into consideration the char- acteristics of the upper-level zonal winds in various ways, as described below.
19 Read more
The quasi-biennial oscillation is a regular variation of the zonal winds that blow high above the equatorial lower stratosphere. Strong zonal winds in the strato- sphere travel in a tropical belt (~15˚S to 15˚N) around the planet, and every 14 months or so, these winds completely change direction (easterly/westerly). This means a complete cycle takes approximately 28 months, making it the most regular slow variation (descending wind speed regime) in the atmosphere after the cycle of the seasons     . The stratospheric quasi-biennial oscil- lations in zonal wind (hereafter, SQBO) are driven by vertically propagating at- mospheric planetary waves (equatorially trapped Kelvin and Mixed Ross by Gravity Waves) that originate from the troposphere and are produced by intense weather systems due to convection and topography. These waves break in the tenuous stratosphere and provide a force to “push” wind and make it descend with time (at a rate of about 1 km per month). Once these high-level winds reach the tropopause, the opposite phase of the oscillation (easterly/westerly phase of QBO) descends from above. It takes roughly 14 months for each reversal to oc- cur. The stratospheric quasi-biennial oscillation is observed at altitudes from about 100 hPa (~16 km) to about 3 hPa (~40 km) . The maximum amplitude is observed in the middle and lower tropical stratosphere, with the easterly phase having larger amplitudes compared to the westerly phase. The westerly shear zones descend more regularly and rapidly than easterly shear zones. The ampli- tude of 20 ms −1 is nearly constant from 5 to 40 hPa but decreases rapidly as the
27 Read more
The zonal mean zonal velocities in the upper tropospheres of the gas giant planets have been well constrained observationally by several decades of observations and tracking of the visible features of cloud tops. In the case of Jupiter, a combination of Galileo, Voyager, and Cassini observations, together with ground-based and Hubble Space telescope observations, indicates zonal winds that are remarkably steady in time [Porco et al., 2003]. In the case of Saturn, with the possible exception of the equatorial jet [Sánchez-Lavega et al., 2007], zonal winds are again found to be relatively steady, although uncertainties remain concerning the reference frame relative to which these should be measured [Anderson and Schubert, 2007; Read et al., 2009]. How these cloud-measured winds vary in height in the opaque atmospheric region below the cloud deck remains unknown, with some studies arguing for an increase in wind magnitude going downward through the cloud layer [Dowling and Ingersoll, 1989; Orsolini and Leovy, 1993; Dowling, 1995], and others arguing for a decrease [Allison, 2000; Lian and Showman, 2008; Liu et al., 2013]. Near the equator, the vertical proﬁle returned by the Galileo probe at 6.5 ∘ N revealed winds increasing with depth [Atkinson et al., 1998].
Figure 14 indicates that there are some significant differ- ences between zonally averaged zonal winds with or with- out height integration. The lower the altitude, the smaller the wind magnitude. There is also a slight change in phase (to aid the eye these are indicated by vertical dashed lines placed at turning points for the weighted winds). This is due to the increased collision frequency at lower altitudes owing to greater density, and the consequent shift in balance between pressure gradient and ion drag. When we look at the averaged diurnal variation of the CHAMP and FPI winds, their phases are almost exactly the same. This would not be the case if the FPI was observing winds dominated by Doppler shifts at an altitude of 190 km, where the phase would be significantly different because the pressure gradient increases its dom- inance at lower altitudes. Comparing the CMAT2 Decem- ber 2007 model zonally averaged zonal winds at 240 km with the height-integrated winds, the most significant difference is for Longyearbyen during quiet conditions, which on calcu- lating overall mean values produces a 19 % difference; dur- ing active conditions, this decreases to a difference of 12 %. The reverse seems to be the case for Kiruna, as the mean per- centage difference increases from 3 % to 14 % between the quiet and active days respectively. Note that the wind speed scales are different for each panel. For each time series there is no simple systematic trend. Figure 15 demonstrates these dissimilarities on a global scale; here, the zonal winds appear to be slightly more westward, as the eastward winds are di- minished and the westward winds enhanced. However, this is not the case for all times of day shown here, and does not visibly affect the wind distributions to any large extent. 6.3 CHAMP cross-track wind procedure
26 Read more
In Fig. 8a, we see the zonal winds derived from HIRDLS V7 for sample day 18 May 2006 and sample pressure levels 1 and 100 mb (top row). In Fig. 8b, we see ERA-Interim for the same sample day and levels (middle row), and Fig. 8c shows their differences (bottom row). In Fig 8a and b, no- tice the large maxima at high southern latitudes and the band of minima along 30 ◦ N for the 1 mb case. For the 100 mb case, we see maxima at high latitudes, with some spots of minima in the tropics. Qualitatively, these plots agree very well. Regarding Fig. 8c, the differences show no systematic biases, and most differences are less than or on the order of ± 5 m s −1 .
11 Read more
during winter at middle latitudes, where the simulated mean zonal winds are mainly westward. On the other hand, win- tertime mean zonal winds are eastward at high latitudes, in agreement with the observations. The simulated mean merid- ional winds are mainly equatorward during summer below ∼ 91 km, also in agreement with the observations. However, the poleward winds typically seen in meteor radar measure- ments during winter are not as evident in the simulations, especially at high latitudes. The simulated SW2 tidal com- ponent exhibits similarities with the observed S2 tide: strong amplitudes in winter and both the spring and fall transition times are characterized by a decrease in the activity of SW2, with the decrease seen in the fall being significantly more pronounced and occurring rapidly at all height levels. On the other hand, the amplitudes of SW2 during summer are con- siderably larger than those of the observed S2, while the SW2 fall decrease occurs earlier (∼ 25 days) and lasts a few more days than in the case of the observed S2. The fall decrease in the simulated total semidiurnal (S2 in Fig. 3) solar tide also takes place ∼ 25 days earlier than in the observations.
10 Read more
We extracted the following fields (when available): ver- tically integrated total column ozone; zonal winds, merid- ional winds, temperatures, geopotential heights, Ertel’s po- tential vorticity (PV), and ozone mixing ratio, on provided pressure levels; and at the surface, mean daily temperature, minimum daily temperature, maximum daily temperature, mean sea level pressure, surface pressure, total precipita- tion liquid water equivalent, and total snowfall liquid wa- ter equivalent. Most raw reanalysis output is available every 6 h (for pressure-level fields) and sometimes up to every 3 h (for surface-level fields), but we computed daily means of all fields for the SSWC. We interpolated pressure-level fields onto a 2.5 ◦ × 2.5 ◦ latitude–longitude grid, while the surface- level fields are maintained at native horizontal resolution. We retained data on provided pressure levels, but we interpolated certain fields (PV and ozone mixing ratio) onto isentropic surfaces. Unless isentropic-level data are provided, we cal- culated potential temperature (θ) from temperature data on pressure levels using Eq. (1):
14 Read more
Numerical simulations of Jupiter’s zonal jets are presented, which are gener- ated with realistic and hyper energetic source. The models are three dimen- sional and nonlinear, applied to a gas that is convective, stratified and com- pressible. Two solutions are presented, one for a shallow 0.6% envelope, the other one 5% deep. For the shallow model (SM), Jupiter’s small energy flux was applied with low kinematic viscosity. For the deep model (DM), the energy source and viscosity had to be much larger to obtain a solution with manageable computer time. Alternating zonal winds are generated of order 100 m/s, and the models reproduce the observed width of the prograde equa- torial jet and adjacent retrograde jets at 20˚ latitude. But the height variations of the zonal winds differ markedly. In SM the velocities vary radially with al- titude, but in DM Taylor columns are formed. The dynamical properties of these divergent model results are discussed in light of the computed meri- dional wind velocities. With large planetary rotation rate Ω, the zonal winds are close to geostrophic, and a quantitative measure of that property is the meridional Rossby number, Ro m . In the meridional momentum balance, the
10 Read more
The influence of the SAM on the ice cover appears more complex (Kwok and Comiso, 2002; Liu et al., 2004; Lefeb- vre et al., 2004) than this annular oceanic response, whose main characteristics are similar at all the longitudes. Indeed, the correlation between the SAM index and the ice extent displays a dipole, with more ice in the Ross Sea and less in the Weddell Sea. This clearly non-annular pattern appears driven by a decrease in sea level pressure in the Amundsen- Bellingshausen Seas when the SAM is high. This induces a deflection of the westerlies towards the south-east around the Peninsula and towards the north-east in the Ross Sector. These winds change the sea ice velocities, the advection of heat by the ocean current and advect also warmer air in the Weddell Sea and colder air in the Ross Sea, resulting in the dipole described above (Lefebvre et al., 2004). Those studies also underline that in some regions, the SAM explains only a small fraction of the internal variability of the system and a lot of other factors must be invoked in order to understand the variability of the Southern Ocean.
13 Read more
The diurnal tidal phases are shown in Fig. 9. The phases are referenced to a longitude of 13 ◦ east. The white contour line labels phase jumps and zero phases. The CMOR phases are shifted as if they would have been observed at the CMOR latitude but at the above-mentioned longitude in the Euro- pean sector. The diurnal tidal phases show a distinct seasonal pattern and latitudinal differences. Throughout the year there are substantial changes in the phases at a given altitude; in particular, at the polar latitudes during the winter months, the phases undergo phase drifts of several hours within a month. Based on the long-term series, Fig. 10 indicates the in- terannual LTC for the diurnal components. For the loca- tions of Andenes and Juliusruh, the diurnal component shows small but significant tendencies. During the summer at An- denes, a westward-directed amplitude gradient is present in the westward wind regime below 85 km, with values of up to 0.3 m s −1 year −1 . Furthermore, there is a northward- directed wind amplitude change during the fall at around 100 km. At the location of Juliusruh, changes take place in the zonal component during the winter, with a tendency to- wards a decreasing diurnal tidal activity above 90 km. How- ever, at Andenes and Juliusruh the zonal and meridional di- urnal tidal amplitudes show only rather small changes from 2002 to 2018. At CMOR changes emerge between 82 and 100 km in January. During the early winter, the LTC shows an increasing diurnal tidal amplitude activity, with values up to 0.4 m s −1 year −1 for the zonal component and almost no
25 Read more
cross correlation diagram are presented in Fig. 10. The first maximum at a positive lag was found at around 4200 days (or 12 yr) with a correlation value of 0.45. These data appear to agree with other, much more detailed reanalysis results (see, e.g. (Sinha and Topliss, 2006), where eastward prop- agating SST anomalies have been identified with character- istic basin crossing times of ∼ 10 yr). As mentioned before, both the minimal numerical model of te Raa and Dijkstra (2002) and our results imply that the SST anomalies predom- inantly tend to propagate westward (though, some counterex- amples were found in our setup, as discussed in the previous section). In reality, wind-driven surface currents (most no- tably, the Gulf Stream in the case of the North Atlantic, as reported by Sinha and Topliss, 2006) definitely affect the cir- culation of such anomalies. Nevertheless, what is of impor- tance here is the order of magnitude agreement between the observed basin crossing timescale of an SST patch and the lag between meridional and zonal temperature differences.
Variability ranging from short to decadal time scales also occurs in a purely dynamical global circulation model of the atmosphere which, without zonal asymmetry (James and James, 1989, 1992), generates a circumpolar storm track, as represented by the Southern Hemispheric atmospheric flow. A physical mechanism inducing long-period variability has been demonstrated as a wobbler-type regime, describing the interaction between the life cycles of cyclones and the zonal mean flow (James et al., 1994; James and Dodd, 1996). The zonally averaged mean flow patterns propagate slowly pole- ward through the mid-latitudes with a velocity of 0...2 m/s (observed a half a century ago by Riehl et al., 1950), and create intermittent behaviour on a wide range of time scales. To investigate the origin of atmospheric variability of the Northern Hemisphere, localised single and double storm tracks have been simulated by Frisius et al. (1998) and Franzke et al. (2000) with a global circulation model forced by anomalies superimposed on the zonally symmetric heat- ing. The vertically averaged stream function shows various kinds of low-frequency variability with a prominent retro- grade wave. Its period near 50 days has been confirmed by observations in the northern Pacific (Kushnir, 1987 and oth- ers), and the underlying physical mechanism has been iden- tified as a spatial resonance regime (Franzke et al., 2000), which has also been found in a single layer ocean model (Sura et al., 2000). So far, the analyses of low-frequency variability modelled by simple GCMs are based on standard statistics and physical methods, whereas more sophisticated nonlinear systems analysis methods have not yet been ap- plied.
13 Read more
3.2 Influence on the polar vortex and anomalous SPWs From previous publications, it is already known that a warm- ing (cooling) of the high-latitude stratosphere (mesosphere) and related changes in the dynamics are generally connected with PW activity. This leads us to the hypothesis that the main GWD enhancement effect is due to SPW modulation, and this will be investigated in this subsection. In Fig. 5, we show the geopotential height (as contour lines) and the zonal wind (using color coding) as a polar plot at 35 km, i.e., 5 km above the region of GW forcing, for the H3 (Fig. 5a), H7 (Fig. 5b) and Ref simulations (Fig. 5c). The panels rep- resent the last 30 d of analysis. The position of each GW hotspot is illustrated by the boxes, H1 (black) to H8 (vio- let), in Fig. 5c. The polar vortex of the Ref simulation is sta- ble (not displaced or split) and located near the North Pole (Fig. 5c). Between 30 and 55 ◦ N, the zonal wind of the Ref simulation is easterly in one part of the EA/NP region due to the Aleutian High (AH). This means that the GW forc- ing, which normally acts against the westerly zonal mean zonal wind, locally strengthens the zonal wind. Between 55 and 90 ◦ N there is a strong westerly wind between East Asia and Alaska; thus, the GW forcing there acts locally against
17 Read more
2. When we include winds in the model, the salt intru- sion increases by an average of 12 km. After more de- tailed investigation of the respective effects of local and remote winds, we find that the local wind pushes the plume water against the western shore in the estuary, lowers the water level in the eastern part of the estuary and increases the bottom landward flow, favoring an in- crease in salt intrusion. It also generates horizontally- sheared estuarine circulation and segregated salinity distribution. The remote wind pumps saltier water into the estuary mouth, increases the vertical mixing on the shelf and generates a change in the salinity pattern such that there is a noticeable increase in surface salinity in the estuary, but only a slight increase in the bottom salinity. The increases in salt intrusion due to the re- mote wind and the local wind are comparable. The re- mote wind effect is somewhat similar to the effect of a rise in sea level, which enhances intrusion by increasing the water level and estuarine circulation.
21 Read more
These m odels d em o n strate th a t th e velocity stru c tu re of th e cool wind has a strong effect on th e R am an Unes, b o th in term s of th e intensity profile and th e polarization stru c tu re . T he smaUest differences betw een th e const ant- velo city wind and th e accelerating wind m odel occurs a t th e larger binary separations, particu larly for winds w ith a high m ass-loss ra te . This is presum ably because the Une form ation in th e accelerating m odel is occuring in a region where th e wind is close to its term inal velocity and Uttle scatterin g is occuring in th e steeply accelerating region of th e wind. M odel ( 6) shows th a t th e veloc ity law m ay be im p o rta n t lower mass-loss ra te m odels, even a t wide binary separations, since th e scatterin g volume encom passes th e accelerating region of th e wind, giving rise to changes in polarization stru c tu re in th e blue Une-wing (where th e sc atterin g is occuring in th e p a rt of th e wind approaching th e p aren t photon source). Clearly th e velocity s tru c tu re becom es m ost im p o rta n t when th e binary separation is smaU, and th e Une fo rm atio n is occuring in a region of th e wind w ith large velocity gradients. M odel (c) shows th a t th e R am an Une intensity is stronger in th e accelerating wind m odel, m ainly because th e wind density is m uch higher a t smaUer separations th a n in th e co n stan t velocity m odel.
260 Read more
Annually, both HSLC significant severe reports and nulls have an April peak, followed by a decrease through the summer and early fall with only a weak secondary maximum in October (Fig. 3.6). December was the only month with a higher number of nulls than significant reports, suggesting a decrease in warning skill during that month (although the sample size is rather small compared to most other months). When breaking the annual cycle down by subjectively defined regions (see Fig. 3.7e), many similarities to previous climatologies of severe weather (e.g., Brooks et al. 2003; Doswell et al. 2005) became evident (Fig. 3.7a). Fall and winter (September-February) HSLC significant severe reports predominantly occurred in the South Atlantic and Lower Mississippi Valley regions. In the spring (March-May), reports became increasingly common in the Southern Plains and the Upper Midwest. By summer (June-August), the Northern Plains accounted for a large fraction of HSLC significant severe reports. HSLC significant tornado reports (Fig. 3.7b) have a February-April maximum in the Lower Mississippi Valley and South Atlantic, accounting for most of the overall distribution shown in Fig. 3.3 and consistent with the annual cycle of Guyer et al. (2006). A clear annual minimum in HSLC tornadoes occurred in the summer, presumably because CAPE is typically high and shear is typically low over much of the U.S. The HSLC significant wind reports (Fig. 3.7c) have similar trends to the total HSLC significant reports (cf. Fig. 3.7a), largely because the majority of HSLC reports are winds. The HSLC significant hail threat (Fig. 3.7d) was largely nonexistent through the winter, with a rapid increase in spring. As with severe winds, by summer, the threat was primarily in the Plains and Upper Midwest.
142 Read more
A vital component in determining the habitability of a planet is the influence of the planet’s host star. In particular, the activity and winds resulting from the magnetic field of an exoplanet’s host-star will play a critical role in ensuring that the planet will be able to sustain a sufficient atmosphere to ensure that life can develop and thrive. In our own Solar system, Mars stands as an example of the destructive power winds can have on a planet’s atmosphere. Over the four and a half billion year history of our Solar system, Mars’s once thick atmosphere has been stripped by the wind of our Sun . Earth has been able to maintain the atmosphere required to support life due to its protective magnetic field.
gradient along the West Coast bringing NW stronger winds. As the front moves across the country it displaces the northwesterly airflow ·bringing southwesterlies behind it. On occasions the northwesterly will persist for several days and the direction remains quite constant through the tropo sphere and well into the stratosphere. On such occasions altocumulus lenticular wave clouds are usually evident much of the time except when a solid sheet of altocumulus is formed streaming back from some distance to the lee of the Alps. This is known as the nor'west arch. The arch is associated with the lee wave phenomena as it is quasi.
386 Read more