AMTAtmospheric Measurement TechniquesAMTAtmos. Meas. Tech.1867-8548Copernicus GmbHGöttingen, Germany10.5194/amt-8-97-2015An evaluation of COSMIC radio occultation data in the lower atmosphere over the Southern OceanHandeL. B.luke.hande@gmail.comSiemsS. T.MantonM. J.LenschowD. H.https://orcid.org/0000-0003-4353-0098School of Earth, Atmosphere and Environment, ARC Centre of Excellence for Climate System Science, Monash University, Melbourne, AustraliaNational Center for Atmospheric Research,
Boulder, Colorado, USAL. B. Hande (luke.hande@gmail.com)9January2015819710718August201419September201412December201415December2014This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://www.atmos-meas-tech.net/8/97/2015/amt-8-97-2015.htmlThe full text article is available as a PDF file from https://www.atmos-meas-tech.net/8/97/2015/amt-8-97-2015.pdf
The global positioning system (GPS) radio occultation (RO) method is a
relatively new technique for taking atmospheric measurements for use in both
weather and climate studies. As such, this technique needs to be evaluated
for all parts of the globe. Here, we present an extensive evaluation of the
performance of the Constellation Observing System for Meteorology,
Ionosphere, and Climate (COSMIC) GPS RO observations of the Southern Ocean
boundary layer. The two COSMIC products used here are the “wetPrf” product,
which is based on 1-D variational analysis with European Centre for
Medium-Range Weather Forecasts (ECMWF), and the “atmPrf” product, which
contains the raw measurements from COSMIC. A direct comparison of temporally
and spatially co-located COSMIC profiles and high resolution radiosonde
profiles from Macquarie Island (54.62∘ S, 158.85∘ E)
highlights weaknesses in the ability of both COSMIC products to identify the
boundary layer structure, as identified by break points in the refractivity
profile. In terms of reproducing the temperature and moisture profile in the
lowest 2.5 km, the “wetPrf” COSMIC product does not perform as well as an
analysis product from the ECMWF. A further statistical analysis is performed
on a large number of COSMIC profiles in a region surrounding Macquarie
Island. This indicates that, statistically, COSMIC performs well at capturing
the heights of main and secondary break points. However, the frequency of
break points detected is lower than the radiosonde profiles suggest, but this
could be simply due to the long horizontal averaging in the COSMIC
measurements. There is also a weak seasonal cycle in the boundary layer
height similar to that observed in the radiosonde data, providing some
confidence in the ability of COSMIC to detect an important boundary layer
variable.
Introduction
The structure and dynamics of the atmospheric boundary layer (ABL) not only
directly impact the weather, through the transport of scalars such as water
vapour, but also the climate, most obviously through their role in the
formation and dissipation of clouds. The ABL height is an important variable,
which is controlled by a balance of large-scale subsidence tending to
decrease the ABL height and turbulent processes tending to increase the ABL
height . The exact definition of the ABL height is ambiguous,
making it difficult to quantify and study, particularly as routine
observations of the depth of the boundary layer are generally not available
over much of the globe. This problem is exacerbated over remote locations,
such as the Southern Ocean, where in situ observations are sparse. Given that
clouds over the Southern Ocean is responsible for large biases in modelled
net radiation , it is important to understand the
fundamental processes at work in this region, which is dominated by the
presence of boundary layer cloud year round .
present a climatology of Southern Ocean clouds from
CloudSat, and identify weaknesses in the ability of CloudSat to
identify low clouds due to interference with the surface. This finding was
reinforced by , who found similar difficulties with other
satellite products. The height of clouds is strongly correlated with the
height and structure of the boundary layer. present a
detailed study of the structure of the ABL over the Southern Ocean from
in situ measurements taken from Macquarie Island (54.62∘ S,
158.85∘ E). The observations from radiosonde data suggest that the
ABL is shallow and often decoupled, a feature manifested as multiple layers
in the lowest few kilometres, and these features are not well captured in a
state-of-the-art reanalysis data set from the ECMWF. It was shown that the
reanalysis data set had a median primary inversion about 200 m lower than
the radiosonde data. An analysis of proxy cloud fields from the radiosondes
indicated that the low-level clouds are not typically capping a well-mixed
boundary layer, in stark contrast to the well-studied subtropical
stratocumulus in the Eastern Pacific and Atlantic (e.g. ). Furthermore, multiple cloud layers were observed to exist
both within, and above the ABL. This supports earlier field observations of
boundary layer decoupling in regions with less subsidence as typified in the
First Aerosol Characterization Experiment (ACE-1) . During ACE-1, as well as the Southern Ocean Cloud Experiments
(SOCEX) , a main inversion in virtual potential temperature
was observed below 2 km from aircraft data, with a weaker inversion below
the main inversion. Cloud was observed throughout this decoupled boundary
layer.
Another distinctive feature of the Southern Ocean is high wind speeds and
wind shear , producing some of the largest observed
wave heights on the globe . These conditions lead to the
possibility of significant sea spray being injected into the boundary layer.
This could have an, as yet, unaccounted for effect on the thermodynamics of
the boundary layer, as well as the cloud microphysics . With
observations supporting an increase in the strength of the Southern Hemisphere
westerlies over recent decades , the potential long-term impact of these effects on the Southern Ocean boundary layer, as well as
the associated clouds, could be significant.
demonstrated the usefulness of using global positioning
system (GPS) radio occultation (RO) data to study the ABL height. They found that
estimating the ABL height from the refractivity profile provided good
agreement with radiosonde and reanalysis data sets. Most commonly used
methods for determining the ABL height from GPS RO data involve identifying
large gradients in the refractivity profile . A global
analysis of ABL heights was performed by from GPS RO data. Their
technique involved looking for a break point, or first-order discontinuities,
in the refractivity profile, which served as an indicator of the ABL top. It
was shown to agree well with boundary layer heights estimated from high-resolution radiosonde observations, particularly in the subtropical high-pressure regions where there is often a well-defined decrease in moisture
above the main inversion. use a similar technique to study the
global variability of the ABL height. The authors find good agreement of ABL
heights between COSMIC and radiosonde data on seasonal timescales.
Similarly, present a climatology of ABL heights using several
methods to estimate the heights from a number of different measurement
systems. That study concludes that ABL heights based on the profile of
refractivity do not agree with those based on gradients of other
meteorological variables, particularly in the presence of clouds. There are
large differences between different methods to calculate the PBL top in the
presence of clouds, due to large humidity lapses over cloud top which can
commonly lead to higher PBL heights when calculated from the humidity
gradient. This conclusion is quite poignant, particularly for a cloud-dominated region such as the Southern Ocean.
The aim of this study is to evaluate the performance of the GPS RO technique
of measuring boundary layer height, and other significant inversions, as well
as the ability of the “wetPrf” COSMIC product to reproduce the temperature
and moisture profiles within the boundary layer. An evaluation of this COSMIC
data product is needed in this region because the structure of the boundary
layer is unlike that of the tropical and subtropical high-pressure region,
where the break point method for determining the ABL height has been shown to
perform well.
Observational and analysis dataCOSMIC
The Constellation Observing System for Meteorology, Ionosphere, and Climate
(COSMIC)/Formosa Satellite 3 (FORMOSAT-3) is a constellation of six identical
microsatellites each carrying a GPS RO receiver . This
allows for around 1500–2000 soundings per day around the globe, from 2006
onwards. The COSMIC measurement process is outlined by ,
and summarized below. The primary measurement is of the Doppler shift of a
radio signal that is emitted from the GPS satellite, occulted by Earth's
atmosphere, and received by the Low Earth Orbiting satellite on the opposite
side of the atmospheric limb. From this, a bending angle is derived, then the
refractivity can be computed as a vertical integral of the bending angle from
the top of the atmosphere down. The limb scanning geometry, either rising or
setting occultations, is produced by the relative motion of the two
satellites.
The raw measurements of the refractivity are used to identify the ABL height
using the common technique of identifying break points in the refractivity
profile, to be discussed in Sect. 3. This technique amounts to computing the
vertical derivative of the refractive index, essentially reverting back to
the bending angle measurement. This “atmPrf” data set contains
approximately 802 data points in the lowest 3 km, and will be referred to as
the COSMICraw data set, where appropriate.
In the
neutrally charged atmosphere, the refractive index (N) can be related to
the pressure (p), temperature (T) and water vapour pressure (e) by
N=77.6pT+3.73×105eT2,
where T is in Kelvin, and p and e are in hPa. With the aid of the
hydrostatic equation, Eq. () can be used to estimate
vapour pressure if temperature is specified, and vice versa. In this study,
the “wetPrf” product was also used, which combines the raw observations
with moisture information from the ECMWF TOGA 2.5 analysis using 1-D
variational analysis. The ECMWF analysis product is used as a first guess for
moisture below 10 km. The resulting profile is interpolated onto 100 m
levels to produce the “wetPrf” profiles. Therefore in this data set,
information on moisture and temperature is available at the expense of the
high vertical resolution available in the raw refractivity measurements. The
refractivity used in the “wetPrf” data set is the analysed refractivity,
not the raw measurements. There are, on average, 31 data points in the lowest
3 km of the profiles over the Southern Ocean, and 400 levels available for
the whole sounding. For the sake of clarity, this data product will be
referred to as the COSMICwet data set. The profiles are constructed
from 50 km long horizontal transects which cover the lowest 3 km.
Therefore, the profiles from both COSMIC products would represent an average
of the conditions over this line.
ECMWF analysis
The European Centre for Medium-Range Weather Forecasts (ECMWF) has a number
of data products providing global coverage of various atmospheric variables.
The ECMWF TOGA 2.5 global Upper Air Analysis data set is
used here to understand the influence of the background data in the 1-D
variational data assimilation. The process of 1-D variational analysis uses
the estimates of moisture from the ECMWF data to produce the
COSMICwet measurements. This analysis data set is not independent
of the other data sets considered here. The Macquarie Island radiosonde
profiles are used in the assimilation process, however their contribution to
the reanalysis data is weighted depending on the error characteristics of
this data set. These error characteristics are determined by comparing these
observations to others in this regions, mostly from satellite-based platforms
over the Southern Ocean. When there is agreement between the various
observations, the radiosonde data receive a higher weighting, and vice
versa. These radiosonde data will be used for the evaluation of the
thermodynamics for a limited number of cases. In addition to the radiosonde
data, the ECMWF also assimilates the GPS RO data used in this study.
Atmospheric profiles from ECMWF represent box-averaged quantities. Thus,
these profiles represent the regional conditions over a larger portion of the
ocean than the radiosonde profiles.
Macquarie Island
Macquarie Island, located at 54.62∘ S, 158.85∘ E, is one of
the few Southern Ocean islands with a dedicated meteorological station. Here,
radiosondes are released twice daily from an altitude of 8 m, with direct
exposure to the prevailing westerly winds. The data set used here (MAC) consists of
the 10 s vertical resolution soundings covering the period 1995–2014,
consisting of 13 396 soundings. On average, there are 171 measurements in
the lowest 3 km of the atmosphere. The profiles from the radiosonde
represent a point measurement, and as such would be much more representative
of the local conditions around Macquarie Island, rather than the regional
conditions in the Southern Ocean. The difference in measurement techniques
between the three data sets will contribute to differences in their
respective representations of the atmospheric conditions.
The lack of observations at these high latitudes compared to other regions
with better coverage of observations reduces the accuracy of numerical
weather prediction . As a result, the location and extent of
cold fronts, for example, can be inaccurate. The frequency of fronts passing
over Cape Grim, Tasmania, was determined by to be up to twice a
week.
Figure shows an example of a mean sea level pressure (MSLP)
chart over much of the Southern Ocean, with the approximate location of
Macquarie Island shown by the red dot. It is interesting to note the
complicated frontal structures associated with the low-pressure systems over
the Southern Ocean south of Australia. Hence, determining the exact synoptic
conditions during each COSMIC or MAC profile may be prone to error.
MSLP chart for 2 May 2007 at 12 Z. The approximate location of
Macquarie Island is shown by the red dot. (Source: Australian Bureau of
Meteorology.)
Determining the ABL depth
A method for determining the height of the atmospheric boundary layer similar
to is implemented for this study, and outlined below. We look
for a break point in the N(z) profile between 100 and 2500 m by defining
an approximately 300 m sliding window and calculating the gradient of a
linear regression of the form Az+B within the window. The break point,
which we use as an estimate of ABL height, is defined as the maximum
difference of A from the windows immediately above and below the break
point. A minimum value of 50 km-1 for the gradient of the window
immediately below the break point of the main inversion is required. A
detailed description of the method is outlined in , including an
example of how the method identifies inversions in sounding profiles. A
secondary break point, or inversion, is defined in the same way, with a
maximum height of 80 % of the height of the main inversion, and a minimum
value of 40 km-1 for the gradient of the linear regression immediately
below the secondary inversion. The requirement for having a weaker inversion
below a main inversion ensures consistency with previous observations of the
Southern Ocean boundary layer , and is also
commonly observed in other marine environments .
The magnitude of the gradient defining the secondary inversion is weaker than
the main inversion, and hence differs from . This value was
chosen so the mean and standard deviation for the height of the secondary
inversions, and also the frequency of occurrence for the MAC data set, were
roughly the same as , who defined the ABL height based on the
virtual potential temperature profile from soundings. Changing the value of
the gradient below the break point by ±5 km-1 had little effect on
the height of inversions, with changes less than 15 m, but changed the
frequency of occurrence by approximately ±16 % for secondary
inversions.
The above method for determining the ABL height relies on identifying changes
in the refractivity profile. However, it is changes in the temperature and
moisture which are often used to define the top of the ABL. So at this point
it is worthwhile considering how changes in the refractivity relate to
changes in temperature and moisture. Differentiating
Eq. () with height gives
dNdz=77.61Tdpdz-77.6pT2dTdz+3.73×1051T2dedz-7.46×105eT3dTdz.
This shows that gradients in N(z) are linked to gradients in temperature
and vapour pressure, which are of the opposite sign. Therefore, the break
point technique is most sensitive to a temperature increase and a moisture
decrease occurring together. This is typical of a sub-tropical marine
boundary layer. However, showed that this structure only
occurs in around 18 % of radiosonde data analysed over the Southern Ocean.
Both temperature and vapour pressure can increase above the ABL, and in this
case the refractivity may not necessarily change across the ABL top, and
hence no ABL top detected. This was confirmed by tests on idealized profiles
which were constructed from a series of straight-line segments with either a
temperature or moisture increase or decrease inserted into the profile within
the lowest 2 km. The break point method in the refractivity profile often
failed to detect an ABL top in the presence of an increase in vapour
pressure, even if this occurred at the same level as a strong temperature
increase. Obviously this depends on the magnitude of the changes in
temperature and moisture; however, the respective magnitudes were chosen to be
consistent with observations from MAC.
show that the changes in moisture contribute about an order of
magnitude more than changes in temperature to the refractivity profile. This
has the potential to complicate the ABL top detection over the Southern
Ocean, where multiple cloud layers are common, meaning that multiple significant
gradients in moisture may be present in the lowest few kilometres.
Case study evaluation of COSMICBoundary layer height
Here we use the MAC data set to make a direct comparison with spatially and
temporally co-located profiles from COSMIC to evaluate the performance of the
RO technique over the Southern Ocean. COSMIC profiles from within a
2 × 2 degree box around Macquarie Island occurring within ±1 h
of the radiosonde launches were considered to be co-located. In addition to
this, the COSMIC soundings were required to penetrate to within 500 m of the
surface. For the period 2006–2013, only 35 soundings were found to coincide.
The small sample is a result of three constraints: the time window, the size
of the box, and the requirement to penetrate to below 500 m. Relaxing these
constraints makes the sample bigger, but less relevant to the local
conditions around Macquarie Island. The conclusions presented in this
evaluation were drawn from the analysis of all the co-located profiles. However, to emphasize the typical ABL structures encountered over the Southern
Ocean, only the results from four profiles will be shown. These four examples
are shown in Figs. to .
Profiles for 2 May 2007 at 11 Z for MAC (black),
COSMICwet (red), COSMICraw (blue), and ECMWF (green).
Vertical dashed (dash-dotted) line represents the threshold defining main
(secondary) break point.
Profiles for 30 November 2009 at 23 Z for MAC (black),
COSMICwet (red), COSMICraw (blue), and ECMWF (green).
Vertical dashed (dash-dotted) line represents the threshold defining main
(secondary) break point.
Profiles for 15 January 2010 at 23 Z for MAC (black),
COSMICwet (red), COSMICraw (blue), and ECMWF (green).
Vertical dashed (dash-dotted) line represents the threshold defining main
(secondary) break point.
Profiles for 27 October 2010 at 23 Z for MAC (black),
COSMICwet (red), COSMICraw (blue), and ECMWF (green).
Vertical dashed (dash-dotted) line represents the threshold defining main
(secondary) break point.
From the MAC data, Figs. and
represent the case where multiple layers are found in the lowest few
kilometres. These two cases have similar meteorological conditions. Both
profiles represent pre-frontal conditions with northerly winds, and high
values of relative humidity indicates that cloud exists throughout the boundary
layer in both cases. Figure represents a well-mixed
boundary layer with a strong temperature inversion, and a decrease in the
vapour pressure occurring at the same height. The MSLP chart corresponding to
Fig. shows that Macquarie Island is under the influence of a
high-pressure system, centred just south of Tasmania. There is a sharp drop
in the relative humidity just over 1000 m, indicating a well-defined cloud
top at the same height. This structure represents a typical boundary layer,
not unlike those found in the sub-tropics where the break-point method on the
refractivity profile has been found to work well . Finally,
Fig. shows no distinctive features, and a
more-or-less stably stratified layer extending from about 500 m to above
2.5 km. This final profile is also under the influence of a high-pressure
system to the north which produces westerly surface winds. In all the
profiles, the black lines represent the MAC profile, the red is the
COSMICwet product, the green is the background ECMWF analysis
profile, and the blue refractivity profile is the raw refractivity
measurements from the COSMICraw product.
The heights of any main and secondary break points detected in the various
data sets are shown in Table . The height of the break
points in the refractivity profile (N-bp) are shown for all data sets.
However, the heights from the ECMWF data are not shown because the vertical
resolution is too low for a 300 m sliding window. As a more conventional
measure of any main and secondary inversions, the gradient in virtual
potential temperature (dθvdz) in
the MAC data set is also shown.
Main and secondary inversion heights for MAC and COSMIC using the
refractivity profile break point method (N-bp) and the dθvdz method for MAC.
COSMICwet N-bp COSMICraw N-bp MAC N-bp MAC dθvdzProfileMainSecMainSecMainSecMainSecFigure ––––1909–1188494Figure 907–1187–1178–1069–Figure 495–595–23531262499178Figure ––––663520––
Figure shows two clear inversions in virtual potential
temperature in the MAC data set, however only one break point in the
refractivity profile is detected. The vapour pressure increases above both
temperature inversions at about 500 and 1200 m, so that the vertical change
in refractivity is mostly cancelled out by the coincident increases in
temperature and vapour pressure. The red profile shows that the
COSMICwet product has the same qualitative behaviour as MAC, however
it is consistently slightly warmer and more moist. There are no break points
detected here. Interestingly, the higher vertical resolution of the
COSMICraw product, shown as the blue refractivity profile, also fails to
detect any break points. The final panel shows the absolute magnitude of the
gradient in refractivity within a 300 m window. The dashed line and the
dash-dotted line indicate the thresholds for the main and secondary inversion
respectively. Gradients in the refractivity of the COSMICwet and
COSMICraw products do not agree in this example.
An example of a well-mixed boundary layer is shown in
Fig. . There is a strong temperature increase and a
corresponding moisture decrease around 1100 m. This feature is identified by
both the break point method, as well as the virtual potential temperature
gradient method in the MAC data. Here, the break points in the COSMIC
profiles show very good agreement with the MAC data set. The COSMICraw
product identifies the break point at the same location as the main
inversion in the MAC data. However, the gradient in the refractivity is much
smaller. The COSMICwet product identifies a break point about 200 m
lower than the other data sets.
Another decoupled boundary layer is shown in Fig. .
Here the strongest inversion is at 500 m, with a weaker inversion aloft at
2200 m. The higher inversion is detected by the break point method. However,
since there is an increase in both moisture and temperature at 500 m, the
break point method fails to detect the lower one. The COSMICwet
product has a break point in the refractivity profile at 495 m, nicely
coinciding with the main inversion in MAC. Similarly, the COSMICraw
product identifies a break point at 595 m, in approximately the same
location. Notice that there is a strong gradient in the refractivity profile
from MAC around 600–700 m. This is not identified as a break point since the
difference in the gradients between adjacent windows is not larger than those
associated with the feature around 1200 m. Also notice that the refractivity
gradients of the two different COSMIC products agree very well.
According to the MAC profile in Fig. , there are no
significant features in either the temperature or vapour pressure. One would
expect no break points or virtual temperature inversions to be detected,
which is true for all but the MAC data set. Here there are two break points
in the refractivity profile associated with some slight variability in the
vapour pressure between about 300 and 700 m.
As a general observation from the 35 co-located profiles, the break point in
the refractivity profile from either COSMIC products rarely aligns with a
virtual potential temperature inversion from the high-resolution MAC
soundings. The COSMICraw product identifies marginally more break
points (16 main and 9 secondary) than the COSMICwet product (15
main and 7 secondary), and there appears to be no systematic difference in
height between the two COSMIC data products, or the MAC data set. The common
method for identifying the ABL top by identifying large gradients in virtual
potential temperature would be inappropriate to use on the
COSMICwet data. The diagnostic variables from COSMICwet,
such as virtual potential temperature, which are derived from a combination
of the ECMWF analysis and the raw refractivity (which is in turn derived from
the bending angle, which is derived from the first-order measurement of a
Doppler shift) are not always consistent with in situ soundings. The
COSMICwet variables can sometimes be unphysical, such as having
superadiabatic layers, as shown in Figs.
and .
Thermodynamics
Here we present an evaluation of the ability of the COSMICwet
product and the ECMWF data to reproduce the temperature and moisture profiles
of the MAC soundings. The root mean squared error (RMSE) for temperature and
vapour pressure, calculated using the differences between MAC and
COSMICwet, and MAC and ECMWF at three levels in the atmosphere are
shown in Table . In order to reduce interpolation
errors of the data sets, the closest level to 500, 1500 and 2500 m were
used as the three levels. The RMSE for each co-located profile and each
variable is defined as
RMSE=∑l=13(MACl-COSMICwet,l)2,
where MACl is the observed variable from the MAC profile at level l,
and COSMICwet,l is the same for the co-located
COSMICwet profile. The RMSEtotal for each variable is
just the root mean squared error of each co-located RMSE for that variable.
That is,
RMSEtotal=∑p=135RMSEp2,
where RMSEp is the RMSE for each co-located profile.
The quantitative analysis shown in Table indicates
that overall, the COSMICwet product is poorer than the ECMWF data
at reproducing the MAC temperature and vapour pressure. Out of the four
profiles shown earlier, only the temperature in Fig.
and the vapour pressure in Figs.
and from COSMICwet perform better than ECMWF.
Over the 35 co-located profiles, the ECMWF data outperform COSMICwet for temperature and vapour pressure, showing the lowest
RMSEtotal for both these variables. This is likely due to the fact
that the MAC soundings have been assimilated into the ECMWF data set used
here.
Qualitatively, it can be seen that the background ECMWF profiles fail to
capture any of the virtual potential temperature inversions which would
typically define the ABL top. The COSMICwet product shows the same
behaviour as the background ECMWF data. COSMICwet does appear to
have slightly more variability in most of the 35 co-located profiles, however
it often produces unphysical superadiabatic layers – for example, in
Figs. and .
Figure is interesting in that the COSMICwet
profile appears to show the same features in the virtual potential
temperature as the MAC data, only offset by several degrees. This raises the
possibility that, given a higher resolution, and more accurate representation
of either the temperature or moisture for the 1D-Var process, the performance
of the COSMICwet data in reproducing the thermodynamics and ABL
height could be improved.
Main refractivity break point for MAC (black), COSMICwet
(red), COSMICraw (blue).
identify horizontal heterogeneity as a potential source of
error in the GPS RO profiles in the neutrally charged atmosphere. In order to
estimate this effect, we consider the impact of a front on the results. An
approximate distance to the nearest front, based on MSLP charts, is given in
Table . The distance to the nearest front is given in
5 degree increments in order to reflect the inherent uncertainty in the
precise location of the frontal system. Figure is the MSLP
chart for the profile shown in Fig. , and shows
Macquarie Island under the influence of a northerly pre-frontal air mass.
There does appear to be a relationship between the performance of
COSMICwet in reproducing the thermodynamics, and the structure of
the ABL, as well as a weak relationship to the synoptic meteorology. Analysis
of the four best and four worst performing COSMICwet profiles, as
judged by the RMSE, showed that the best performance of COSMICwet
in reproducing the thermodynamics occurred when the profile was stably
stratified with no, or only weak inversions and little variability in the
profile. These four profiles were typically closer to a cold front,
suggesting that the influence of a front is to produce a stably stratified ABL
with no strong inversions. On the other hand, the four worst performing
profiles in reproducing the moisture and temperature mostly represented well-mixed ABLs of between 500 and 1200 m depth, with strong temperature inversions
and a decrease in vapour pressure occurring together.
Figure is one of the four worst performing profiles,
which shows a well-defined temperature inversion along with a decrease in
moisture around 1000 m. These profiles with strong inversions tended to be
further away from a front. showed that reanalysis products
typically have difficulty capturing strong changes in temperature or moisture
near Macquarie Island. Hence, a possible explanation for this is the
difficulty of the background ECMWF data to identify large gradients in
temperature or moisture, and the influence this has on the
COSMICwet product.
Root mean squared error for COSMICwet and ECMWF data sets
for the temperature (Temp) and vapour pressure (VPres). The approximate
distance to a front is also shown in degrees. The letter indicates whether
the front is to the west (W) or east (E) of Macquarie Island. The bottom row
shows the RMSEtotal for all the 35 co-located profiles.
To gain a broader appreciation of the performance of both the COSMIC
products, we present a statistical analysis of the height and occurrence of
main and secondary inversions. COSMIC RO data from a 10×10 degree box
around Macquarie Island are used, in order to gain a good statistical sample
size. In total, this amounts to 7768 profiles for the COSMICwet
product, and 7469 for the COSMICraw product over the period
2006–2013. Previous studies show that there are
only very weak diurnal and seasonal cycles in thermodynamic and cloud
properties over the Southern Ocean. Hence, any difference in the temporal
distribution of the two data sets should not affect the statistics.
Figures and show the distribution of
main inversions and secondary inversions from both COSMIC products and MAC.
Secondary refractivity break point for MAC (black),
COSMICwet (red), COSMICraw (blue).
A main inversion was detected in 3559 of the COSMICwet soundings,
and a secondary inversion in 2002 cases. For the COSMICraw product,
a main inversion was detected in 3622 soundings, and a secondary inversion in
2210 profiles. Finally, for the MAC data set, a main inversion occurred in
8944 soundings, and a secondary inversion in 5136 soundings. The statistics
for the main and secondary break points are shown in
Table .
From Table , it can be seen that the relative frequency
of the heights of the inversions are well represented in both COSMIC data
sets. This can also be seen in Figs.
and , where the distribution of the inversions is very
similar between the three data sets. The COSMICwet product tends to
have slightly higher and less frequent main and secondary break points than
the COSMICraw product; however, the difference between the two
COSMIC products is small. There is an anomalously high frequency of secondary
inversions below 500 m in the COSMICwet data which is often
associated with large gradients in moisture near the surface. According to
Table , the frequency of occurrence of the two break
points is significantly less in both COSMIC products compared to MAC.
Therefore, the difference in vertical resolution between the two COSMIC
products does not influence the frequency of main and secondary break points
significantly. The statistics for the MAC data set are close to that of
, who use the gradient in virtual potential temperature to
define the inversion heights. This implies that, statistically, the method of
attributing break points in the refractivity profile to ABL interfaces is
appropriate. However, there are intrinsic uncertainties in the measurement of
the refractivity profile from the COSMIC products, for example the
superadiabatic layers mentioned in the previous section. In terms of
representing the height of the ABL, both COSMIC products offer an improvement
over a high-resolution reanalysis product from the ECMWF, which was found to
underestimate the height of virtual potential temperature inversions by about
200 m . Note that the ECMWF product is not included here
because the vertical resolution is too coarse to reliably compute break
points.
We also investigated seasonal and diurnal cycles in the height of main and
secondary break points; the statistics are presented in
Fig. . It is encouraging to note that there is a weak
seasonal cycle in the heights of the break points from all data sets, with
slightly higher interfaces in Southern Hemisphere summer than winter. The
cycle is less notable in the secondary break points. December is a notable
exception for main break points in both COSMIC products, but nevertheless,
the 3-month average still preserves the seasonal cycle. However, there is
no clear diurnal cycle in any of the data sets.
Statistics for the main and secondary break point in the
refractivity profile for the MAC, COSMICwet and COSMICraw
products.
MACCOSMICwetCOSMICrawMain break point Frequency (%)66.745.848.5Mean height (m)148114691430Median height (m)147114821413Standard deviation (m)521502517Secondary break point Frequency (%)38.325.729.6Mean height (m)821809795Median height (m)750784733Standard deviation (m)349312308
Seasonal cycle of main (top) and secondary (bottom) break points for
MAC (black), COSMICwet (red), and COSMICraw (blue).
Conclusions
The performance of the GPS RO technique of estimating boundary layer heights
over the Southern Ocean has been evaluated. A direct comparison between
co-located COSMIC RO soundings and high resolution radiosonde profiles from
Macquarie Island show that both COSMIC data products identify fewer boundary
layer interfaces, identified as break points in the refractivity profile. The
method of identifying break points in the refractivity profile as the ABL top
has merit. The tests on idealized profiles indicated that this method can reliably
identify increases in temperature and/or decreases in moisture, but can have
difficulties when both temperature and vapour pressure increase across the
interface. This type of boundary layer structure is commonplace over the
Southern Ocean. The full analysis of the 35 co-located profiles shows that
there are fewer break points detected in both COSMIC products, compared to
the MAC data set. However, when co-located profiles from COSMIC and MAC both
identify break points, the heights of the break points mostly agree.
The ability of COSMICwet to reproduce the temperature and moisture
profiles within the boundary layer was evaluated by comparison with the MAC
soundings. It is shown that the COSMICwet product does not agree
with the MAC soundings as well as the background ECMWF data, even though this
product is tied to the background ECMWF data. This illustrates the potential
problems of deriving thermodynamic information from COSMIC data. However, the
COSMICwet product does show more variability in the vertical
profiles, and the ECMWF data often fail to reproduce large temperature or
moisture changes. This suggests that, given a more accurate and high-resolution background data set for the 1-D variational data assimilation, in
may be possible to improve upon COSMIC data products.
GPS RO profiles from within a 10×10 degree box around Macquarie Island
were used to perform a statistical analysis of the ability of COSMIC to
reproduce the main and secondary break point heights. This indicates that,
statistically, COSMICwet reproduces the heights of break points in
the refractivity profile well, as compared to MAC profiles. However, the
frequency is much less. This is true for the raw refractivity measurements as
well, which have much higher vertical resolution, indicating that the
difference in the frequency of boundary layer interfaces detected is not due
to differences in vertical resolution. The favourable agreement in terms of
height is likely due to the break point detection algorithm using the
vertical gradient of refractivity to identify break points. This essentially
reverts back to the change in the bending angle, which is the fundamental
COSMIC measurement. Differences between the MAC soundings and the COSMIC
products should be expected due to differences in the measurement techniques
between the different data sets used in this study. The different methods of
averaging used to produce each data set would contribute to some of the
differences in the RMSE values presented in the evaluation of the
thermodynamics, as well differences in estimating the ABL height and
frequency.
Finally, all data sets produce a weak seasonal cycle in the heights of the
interfaces, as one would expect, which is gratifying. The ability of the
COSMIC products to reproduce this ABL feature indicates there is some merit
in using the break point of the refractivity profile to identify boundary
layer interfaces. This analysis shows that the COSMIC data product is most
useful when analysed statistically on seasonal, or longer, timescales.
Acknowledgements
The radiosonde data were obtained from the Australian Bureau of Meteorology.
COSMIC data and ECMWF data were obtained from the COSMIC Data Analysis and
Archive Center (CDAAC). This research was supported by Monash University,
Australia. The National Center for Atmospheric Research is sponsored by the
National Science Foundation.Edited by:
T. F. Hanisco
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