A daily climatology of the atmospheric circulation of the Arctic and the associated cloud conditions were determined. These are used for comparisons with the variability of general circulation model, generated circulation, and cloud cover for the same region

Barry, R. G.

Crane, R. G.

English

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(HASA-CH-175628) 2HPIBICJI SKE MODELED
SYHOPTIC CLODD CLIHAIOLOGX OF THE ARCTIC
OCBAH Annual Progress Repor t , Apr. -1984 -
Mar, 1S85 (Colorado Un iv . ) 10 p
HC A02/MF flOl CSCL 04B
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14716
EMPIRICAL AND MODELED SYNOPTIC CLOUD
CLIMATOLOGY OF THE ARCTIC OCEAN
Annual Progress Report
April 1984 - March 1985
to
NASA, Climate Research Program
NAG 5-417
Roger G. Barry (Principal Investigator)
Robert G. Crane*
Cooperative Institute for
Research in Environmental Sciences
University of Colorado
Boulder, Colorado 80309
*Present affiliation:
Department of Geography
University of Saskatchewan
Saskatoon, Saskatchewan, Canada
https://ntrs.nasa.gov/search.jsp?R=19850014961 2020-03-20T18:23:04+00:00Z
The objectives of the project are to derive a daily climatology of the
atmospheric circulation of the Arctic and to determine the associated cloud
conditions. The second part of the project will use these data for comparisons
with the variability of General Circulation Model generated circulation and cloud
cover for the same region.
Year 1 Achievements
A. Atmospheric Circulation.
1) Comparison of synoptic typing schemes:
Various 'objective1 synoptic classification schemes are compared in order
to determine which would give an optimum solution and to examine the question of
how much subjectivity is introduced by the various options exercised by the
analyst. The analysis uses a subset of the twice daily National Meteorological
Center (NMC) grid point data set for 93 grid points north of 60°N. Two of the
more popular synoptic typing techniques are compared, the sum of squares method
developed by Kirchhofer (1973), and a method that employs principal component and
cluster analysis. In the former it is found that different classification schemes
will result from the choice of different threshold values, which set the sum of
squres difference level at which one map is considered to be similar to another,
and by the choice of the minimum group size. For the principal components/cluster
analysis, the clustering is based on the component scores. Two cluster techniques
are used, one employs an interactive procedure to obtain a local optimum for k
clusters using an error sum of squares as a similarity measure. The second
obtains maximum likelihood estimates of the parameters of a multivariate normal
mixture of distributions, assigning a probability of membership to each of the
clusters for every case in the sample. Again an iterative procedure is employed.
It was found, when comparing these techniques, that the synoptic types
produced varied between the cluster techniques, and that different results were
obtained within each technique depending on the number of principal components
retained for the analysis.
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2) Arctic synoptic classification:
Based on the comparisons described above it was decided that the Kirchhofer
classification resulted in the greatest differentiation between groups. By
comparing the results using different threshold values and group sizes it is also
possible to derive an 'optimum1 solution for the Kirchhofer classification. A
further test was carried out to compare the results of a synoptic classification
based on sea level pressure and 700 mb heights. The test showed very little
difference between the two classifications. A preliminary examination of the DMSP
derived cloud cover (see section C) showed that the cloud cover appeared to be
more closely related to the sea level pressure field, and this was therefore
chosen for the final analysis.
A synoptic classification of daily Arctic sea level pressure fields has
been carried out for the ten year period 1973-1982. The classification resulted
in seven synoptic types being identified, with 80 percent of the days being
classified into one of these seven types. The percentage number of days in each
group is 18.1, 13.0, 13.0, 12.2, 9.2, 8.9, and 5.1. A synoptic catalog has been
derived for the ten year period based on this classification scheme. Each day in
the ten year record has been assigned to one of the seven types or is listed as
unclassified. A prelminary analysis of the synoptic catalog suggests that there
is some year-to-year variability in the frequency of particular synoptic
circulation patterns.
B. GISS GCM Results.
Sixteen months of 5 hourly model output results have been obtained from a
control run of the GISS medium resolution GCM. These data include optical depth,
surface pressure, potential temperature, specific humidity, radiative equilibrium
temperature, surface wind speed, surface temperature and various other
geographical grids such as ocean ice, snow amount and temperature, etc. Five day
-3-
averages of these data grids have been produced. The surface pressure, potential
temperature and specific humidty grids are currently being used to derive grids of
sea level pressure distributions. All of the five day grids have been remapped to
the same I, J grid as that used for the NMC grid point data.
C. DMSP Cloud Analysis.
The objective of this phase of the project is to develop a data set of cloud
over maps for the Arctic regions covering a sufficiently long period of time to
allow the results to be compared statistically with previous data sets. This
comparison will serve as a test for the data analysis techniques to be performed
in Year 11. In addition the data set developed in Phase 1 can be used to study
the seasonal patterns of cloud developments, the inter-annual variability of
clouds, and the relationship between mean monthly cloud cover and mean monthly
pressure patterns.
Data Base.
The months of April, May and June of 1979 and 1980 were selected for
analysis. These months give overlap wth previous data sets (Kukla, 1984) and
cover the transition from winter to summer conditions. For each month the cloud
conditions on every third day were manually analyzed for the area north of 70
degrees latitude. The DMSP visual imagery was used to identify areas of cumulus
cloud, stratus cloud and open conditions (less than 50 percent cloud cover). The
DMSP infrared imagery was used to divide the cloud into low, middle or high
cloud. Once the data were extracted they were digitized for later analysis.
Figures 1 and 2 illustrate the frequency of cloud-free conditions in April 1979
and 1980.
-4-
Preliminary Analysis.
Preliminary analysis of the data indicates that:
a) In general the analysis give results which agree with previous data sets.
However, differences in the satellites used and the time of the imagery make
direct comparisons difficult.
b) The difference between cloud-free conditions and a low stratus over areas of
high concentrations of pack ice are the most difficult to separate.
c) Significant changes in Arctic cloud conditions can occur over short time
periods. This can make matching data from images as little as 6 hours apart
difficult.
d) Arctic cloud patterns seem better correlated with surface pressure patterns
than with 700 mb patterns.
e) Due to seasonal changes in the factors responsible for cloud formation the
matching of cloud patterns with synoptic types may have to be performed
separately according to season.
f) Cloud conditions in the Arctic Basin seem to be controlled by large-scale
circulation patterns rather than ice conditions.
g) There are recognizable cloud patterns associated with major Northern Hemisphere
circulation types. For example, a weakening of the Icelandic Low and a North
Atlantic pressure reversal in April 1979 was associated with a decrease in cloud
cover in the Norwegian, Barents and Kara Seas.
h) The cloud analysis occasionally indicates meso-scale systems not shown on the
NWS surface analysis.
YEAR TWO OBJECTIVES
A. Empirical Analysis.
In Year Two we propose to complete the synoptic analysis of the NMC grid point
data, providing a description of the synoptic climatology of the Arctic Basin.
-5-
The cloud data extraction from the DMSP imagery will also be completed and an
analysis made of the relationships between cloud cover and the synoptic scale
atmospheric circulation.
B. GISS Model Analysis.
The synoptic climatology of the GCM will be compared to the 'observed1
circulation from the NMC grid point data. Five-day average cloud cover will be
extracted from the five-hourly GISS model output. These cloud cover grids will be
compared both to the synoptic climatology of the model and to the observed Arctic
cloud cover distributions.
Based on our progress and the results obtained during the first year, we
anticipate completing all of the work by the end of Year Two. Our objectives and
anticipated results remain the same as those outline in the original proposal,
except that the analysis of the synoptic scale atmospheric circulation will be
based on sea level pressure patterns rather than the 700mb height fields.
PUBLICATIONS
Abstracts relating to the synoptic climatological analysis (Crane and Key)
and Arctic cloud cover analysis (Newell and Barry) have been submitted to the
IAMAP meeting in Honolulu in August 1985 (see attachments).
A paper describing the synoptic classification analysis is in preparation by
Key and Crane.
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Mapping Arctic Cloud Cover Using DMSP Imagery for
Spring 1979 and 1980
J.P. NEWELL and R.G. BARRY (CIRES and Department of
Geography, University of Colorado, Boulder, CO 80309).
Arctic cloud patterns in spring are a major deter-
minant of the energy available for sea ice melt. A
cloud data set suitable for application to analysis of
such interactions has been developed by manual
analysis of DMSP visual and infrared imagery for every
third day of April-June 1979 and 1980. Clouds were
classified by type and height.
The cloud patterns undergo a marked transition in
spatial organization and persistence in spring. In
April the Arctic is dominated by regional patterns of
convective cloud and intervals of persistent cloud
free conditions. These patterns are controlled by
changes in the Icelandic Low and Polar Anticyclone.
By June the area is dominated by bands of convective
cloud, associated with cold lows, and numerous small,
temporally-shifting areas of cloud free conditions.
Examples of cloudcover-circulation relationships and
their significance for ice melt are discussed. The
results provide a basis for scaling-up to an Arctic
cloud climatology for spring months using long-term
frequencies of synoptic circulation types discussed in
a related paper by Crane and Key (Symposium M-12).
1. IAMAP/IAPSO
Joint Assembly
2. R. G. Barry
CIRES, Box 449
University of Colorado
Boulder, CO 80309
(303) 492-5171
3. M-ll
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Synoptic Climatology of the North Polar Region
R.G. CRANE (Department of Geography, University of
Saskatchewan, Saskatoon, Saskatchewan, S7N OWO Canada)
J. KEY (Department of Mathematical Sciences,
Univeristy of Alaska, Anchorage, Alaska 99504)
Several 'objective* synoptic circulation typing
schemes are examined using ten years of NMC grid point
data for the North Polar region. The typing schemes
group days based on sum of square differences between
cases, or based on clustering of principal component
scores. The analysis shows that each scheme can
produce different results depending on the input
parameters used, and intercoraparisons of the various
schemes reveal that they can generate rather different
synoptic classifications for the same data set.
An 'optimum1 scheme is chosen to describe the
synoptic scale sea level atmospheric circulation over
the Arctic for the period 1973-1982. These
circulation patterns are compared with five-day
averaged sea level pressure distributions obtained
from the control run of the medium resolution GISS
General Circulation Model.
1. IAMAP/IAPSO
Joint Assembly
2. R.G. Crane
Department of Geography
University of
Saskatchewan
Saskatoon, Saskatchewan
S7N OWO Canada
(306) 966-5666
3. M-12


Empirical and modeled synoptic cloud climatology of the Arctic Ocean

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