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The International Surface Pressure
Databank version 2
Thomas A. Cram
1
*, Gilbert P. Compo
2,3
, Xungang Yin
4
, Robert J. Allan
5,6
, Chesley McColl
2,3
, Russell
S. Vose
7
, Jeffrey S. Whitaker
3
, Nobuki Matsui
2,3
, Linden Ashcroft
8,†
, Renate Auchmann
9
, Pierre
Bessemoulin
10
, Theo Brandsma
11
, Philip Brohan
6
, Manola Brunet
12,17
, Joseph Comeaux
1
, Richard
Crouthamel
13
, Byron E. Gleason Jr
7
, Pavel Y. Groisman
7,14,15
, Hans Hersbach
16
, Philip D. Jones
17,18
,
Trausti J
onsson
19
, Sylvie Jourdain
20
, Gail Kelly
5
, Kenneth R. Knapp
7
, Andries Kruger
21
, Hisayuki
Kubota
22
, Gianluca Lentini
23,‡
, Andrew Lorrey
24
, Neal Lott
7
, Sandra J. Lubker
3
,J
€
urg Luterbacher
25
,
Gareth J. Marshall
26
, Maurizio Maugeri
23
, Cary J. Mock
27
, Hing Y. Mok
28
, Øyvind Nordli
29
, Mark J.
Rodwell
6,§
, Thomas F. Ross
7
, Douglas Schuster
1
, Lidija Srnec
30
, Maria Ant
onia Valente
31
, Zsuzsanna
Vizi
32,¶
, Xiaolan L. Wang
33
, Nancy Westcott
34
, John S. Woollen
35,36
and Steven J. Worley
1
1
National Center for Atmospheric Research, Boulder, CO, USA
2
University of Colorado, CIRES, Boulder, CO, USA
3
NOAA Earth System Research Laboratory, Physical Sciences Division, Boulder, CO, USA
4
ERT, Inc., Asheville, NC, USA
5
Atmospheric Circulation Reconstructions over the Earth Initiative, Met Office Hadley Centre, Exeter, UK
6
Met Office Hadley Centre, Exeter, UK
7
NOAA National Centers for Environmental Information, Asheville, NC, USA
8
School of Earth Sciences, University of Melbourne, Melbourne, Vic., Australia
9
Institute of Geography and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
10
M
et
eo-France, Toulouse, France
11
Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands
12
Centre for Climate Change, Universitat Rovira i Virgili, Tarragona, Spain
13
International Environmental Data Rescue Organization (IEDRO), Deale, MD, USA
14
University Corporation for Atmospheric Research, Boulder, CO, USA
15
P. P. Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia
16
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
17
Climatic Research Unit, University of East Anglia, Norwich, UK
18
Center of Excellence for Climate Change Research/Department of Meteorology, King Abdulaziz University, Jeddah,
Saudi Arabia
19
Icelandic Met Office, Reykjavik, Iceland
20
M
et
eo-France, Direction de la Climatologie, Toulouse, France
21
South African Weather Service, Pretoria, South Africa
22
Department of Coupled Ocean–Atmosphere–Land Processes Research, Japan Agency for Marine–Earth Science and
Technology, Yokosuka, Japan
23
Dipartimento di Fisica, Universit
a degli Studi di Milano, Milan, Italy
24
National Institute of Water and Atmospheric Research (NIWA), Auckland, New Zealand
25
Department of Geography, Climatology, Climate Dynamics and Climate Change, Justus Liebig University Giessen, Giessen,
Germany
26
British Antarctic Survey, Natural Environment Research Council, Cambridge, UK
27
Department of Geography, University of South Carolina, Columbia, SC, USA
28
Hong Kong Observatory, Hong Kong, China
29
Norwegian Meteorological Institute, Oslo, Norway
30
Meteorological and Hydrological Service, Zagreb, Croatia
31
Instituto Dom Luiz, Laborat
orio Associado, Universidade de Lisboa, Lisbon, Portugal,
32
Nicolaus Copernicus University, Toru
n, Poland
33
Climate Research Division, Science and Technology Branch, Environment Canada, Toronto, ON, Canada
34
Midwestern Regional Climate Center, Illinois State Water Survey, University of Illinois at Urbana–Champaign, Urbana, IL, USA,
35
I.M. Systems Group, Inc., Rockville, MD, USA
36
NOAA National Centers for Environmental Prediction, Environmental Modeling Center, Camp Springs, MD, USA
*Correspondence: Thomas Cram, National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307-3000, USA,
E-mail: tcram@ucar.edu
ª2015 The Authors. Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and
reproduction in any medium, provided the original work is properly cited.
†Current address: Centre for Climate Change, Universitat Rovira i Virgili, Tarragona, Spain
‡Current address: Ente Regionale per i Servizi all’Agricoltura e alle Foreste (ERSAF), Milan, Italy
§Current address: European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
¶Current address: Department of Space and Climate Physics, University College London, London, UK
The International Surface Pressure Databank (ISPD) is the world’s largest collection of global surface and sea-level pressure
observations. It was developed by extracting observations from established international archives, through international coopera-
tion with data recovery facilitated by the Atmospheric Circulation Reconstructions over the Earth (ACRE) initiative, and directly by
contributing universities, organizations, and countries. The dataset period is currently 1768–2012 and consists of three data com-
ponents: observations from land stations, marine observing systems, and tropical cyclone best track pressure reports. Version 2
of the ISPD (ISPDv2) was created to be observational input for the Twentieth Century Reanalysis Project (20CR) and contains the
quality control and assimilation feedback metadata from the 20CR. Since then, it has been used for various general climate and
weather studies, and an updated version 3 (ISPDv3) has been used in the ERA-20C reanalysis in connection with the European
Reanalysis of Global Climate Observations project (ERA-CLIM). The focus of this paper is on the ISPDv2 and the inclusion of the
20CR feedback metadata. The Research Data Archive at the National Center for Atmospheric Research provides data collection
and access for the ISPDv2, and will provide access to future versions.
Geosci. Data J. 2:31–46 (2015), doi: 10.1002/gdj3.25
Received: 15 May 2014, revised: 3 June 2015, accepted: 8 June 2015
Key words: surface pressure, sea level pressure, observations, stations, ships
Dataset
Identifier: doi:http://dx.doi.org/10.5065/D6SQ8XDW
Creators: Compo, G. P., J. S. Whitaker, P. D. Sardeshmukh, N. Matsui, R. J. Allan, X. Yin, B. E. Gleason, R. S. Vose, G. Rutledge, P.
Bessemoulin, S. Br€
onnimann, M. Brunet, R. I. Crouthamel, A. N. Grant, P. Y. Groisman, P. D. Jones, M. C. Kruk, A. C. Kruger, G. J.
Marshall, M. Maugeri, H. Y. Mok, O. Nordli, T. F. Ross, R. M. Trigo, X. L. Wang, S. D. Woodruff and S. J. Worley
Title:International Surface Pressure Databank (ISPDv2)
Publisher: Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Labo-
ratory, Boulder, Colorado, USA
Publication year: 2010
Resource type: Dataset
Version: 2.0
Introduction
The International Surface Pressure Databank (ISPD) is
the world’s largest collection of global surface and
sea-level pressure observations. Since its inception in
2002, its development has been facilitated by coopera-
tive efforts between the Global Climate Observing Sys-
tem (GCOS)/World Climate Research Program (WCRP)
Working Group on Observational Data Sets for Reanal-
ysis [2007 to 2011], and the ongoing efforts of the
GCOS Working Group on Surface Pressure and the
international Atmospheric Circulation Reconstructions
over the Earth initiative (ACRE, Allan et al., 2011).
The full observational record is extracted and assem-
bled from established international archives and newly
available collections from more than 60 different con-
tributing organizations, shown in Tables 1 and 2.
The ISPD version 2 (ISPDv2) covers the period
1768–2012. It merges data from three input compo-
nents: observations from land stations, marine observ-
ing systems, and tropical cyclone best track pressure
reports. The land station component was extracted
from many national and international collections of
sea-level pressure and surface pressure. The largest
contributor to this component was the Integrated Sur-
face Database (Smith et al., 2011), which consists of
global hourly and synoptic surface observations col-
lected from many sources. The land stations were
merged following a two-step algorithm to first remove
duplicates within a collection and then remove dupli-
cates between collections (Yin et al., 2008).
The marine component consists of sea-level pressure
observations extracted from the International Compre-
hensive Ocean–Atmosphere Data Set (ICOADS, Woo-
druff et al., 1998; Parker et al., 2004; Woodruff et al.,
2005; Worley et al., 2005; Woodruff et al., 2011), a
global ocean marine meteorological and surface ocean
dataset that is considered the most complete of its kind.
It is comprised of measurements and observations
extracted from many international data sources, includ-
ing ship reports, moored and drifting buoys, coastal sta-
tions, and other marine platforms. ICOADS release 2.4
was used in the ISPDv2 for the period 1952–2008 and
ICOADS release 2.5 (Woodruff et al., 2011) was used
for the period 1785–1951 and 2009–2012.
The tropical cyclone component was taken from the
International Best Track Archive for Climate Steward-
ship (IBTrACS; Knapp et al., 2010). The IBTrACS data-
set consists of global tropical cyclone best track
position and intensity observations, and reports col-
lected from each of the World Meteorological Organi-
zation (WMO) Regional Specialized Meteorological
32 T. A. Cram et al.
ª2015 The Authors.
Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd.Geoscience Data Journal 2:31–46 (2015)
Centers, Tropical Cyclone Warning Centers, and other
national agencies. The IBTrACS Beta version was used
for the years 1952–2006, version v01r01 for 1871–
1883 and 1886–1951, version v02r01 for 1884–1885
and 2007–2008, version v03r02 for 2009–2010, and
version v03r05 for 2011–2012.
The inclusion of various versions of both ICOADS
and IBTrACS in ISPDv2 was the result of using the
most up-to-date data that were available during the
assimilation into the Twentieth Century Reanalysis
(20CR; Compo et al., 2011). This rationale is elabo-
rated upon in Section 2.1.
Table 1. Contributing organizations to the International
Surface Pressure Databank.
1. All-Russian Research Institute of Hydrometeorological
Information World Data Center
a
2. Atmospheric Circulation Reconstructions over the
Earth (ACRE)
a
3. Australian Bureau of Meteorology
a
4. Australian Meteorological Association, Todd Project
team
5. British Antarctic Survey
a
6. Cook Islands Meteorological Service
7. Danish Meteorological Institute
a
8. Deutscher Wetterdienst (DWD)
a
9. Environment Canada, Climate Research Division
a
10. ETH Zurich, Switzerland
a
11. European and North Atlantic Daily to Multidecadal
Climate Variability (EMULATE)
a
12. EUropean Reanalysis and Observations for Monitoring
(EURO4M)/The WMO MEditerranean DAta REscue
Initiative (MEDARE)
13. European Reanalysis of Global Climate Observations
(ERA-CLIM)
14. GCOS Atmospheric Observation and Ocean
Observation Panels for Climate Working Group on
Surface Pressure
a
15. GCOS/WCRP Working Group on Observational Data
Sets for Reanalysis
a
16. Hong Kong Observatory
a
17. Icelandic Meteorological Office (IMO)
18. Instituto Geofisico da Universidade do Porto,
Portugal
a
19. International Best Track Archive for Climate
Stewardship (IBTrACS)
a
20. International Comprehensive Ocean–Atmosphere
Data Set (ICOADS)
a
21. International Environmental Data Rescue
Organization (IEDRO)
a
22. Japan Agency for Marine-Earth Science and
Technology (JAMSTEC)
23. Japan Meteorological Agency
a
24. Jersey Met Department
a
25. Koninklijk Nederlands Meteorologisch Instituut (KNMI;
Royal Netherlands Meteorological Institute)
a
26. Lamont-Doherty Earth Observatory of Columbia
University
27. McGill University, Canada
28. Met Office Hadley Centre, UK
a
29. M
et
eo-France
a
30. M
et
eo-France –Division of Climate
31. Meteorological and Hydrological Service, Croatia
a
32. National Center for Atmospheric Research (NCAR),
USA
a
33. National Institute for Water and Atmospheric
Research (NIWA), New Zealand
34. Nicolaus Copernicus University –Department of
Meteorology and Climatology, Poland
35. Niue Meteorological Service
36. NOAA Climate Database Modernization Program
(CDMP), USA
a
(continued)
37. NOAA Earth System Research Laboratory (ESRL),
Physical Sciences Division, USA
a
38. NOAA Midwest Regional Climate Center at UIUC,
USA
a
39. NOAA National Centers for Environmental Prediction
(NCEP), USA
a
40. NOAA National Climatic Data Center (NCDC), USA
a
41. NOAA Northeast Regional Climate Center at Cornell
University, USA
a
42. NOAA Pacific Marine Environmental Laboratory, USA
43. Norwegian Meteorological Institute
a
44. Ohio State University –Byrd Polar Research Center,
USA
a
45. Oldweather.org
46. Portuguese Institute of Sea and Atmosphere (IPMA),
Portugal
47. Proudman Oceanographic Laboratory, UK
a
48. Signatures of environmental change in the
observations of the Geophysical Institutes (SIGN)
a
49. South African Weather Service
a
50. South Eastern Australian Recent Climate History
(SEARCH) project, The University of Melbourne
51. Tanzania Meteorological Agency
52. University of Abderdeen, Scotland, UK
53. University of Bern, Switzerland
54. University of Colorado –Climate Diagnostics Center
(CDC) of the Cooperative Institute for Research in
Environmental Sciences (CIRES)
a
55. University of East Anglia –Climatic Research Unit,
UK
a
56. University of Giessen –Department of Geography,
Germany
57. University of Lisbon –Instituto Dom Luiz, Portugal
a
58. University of Milan –Department of Physics, Italy
a
59. University of Porto-Instituto Geofisico, Portugal
a
60. University Rovira i Virgili –Centre for Climate Change
(C3), Spain
a
61. University of South Carolina, USA
62. University of Toronto –Department of Physics,
Canada
63. University of Washington, USA
64. World Meteorological Organization –MEditerranean
climate DAta REscue (MEDARE)
65. Zentralanstalt f€
ur Meteorologie und Geodynamik
(ZAMG; Austrian Weather Service)
a
a
Contributors to version 2 (cf. Compo et al., 2011, Table II).
Table 1. (continued)
The international surface pressure databank 33
ª2015 The Authors.
Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd. Geoscience Data Journal 2:31–46 (2015)
Table 2. ISPDv2 dataset collection identifiers and names.
ISPD ID Name Description Period No. stations/records
NCDC
reference NCAR reference Reference publication
0100 ICOADS Release 2.1 Global Marine Surface Observations 1784–2005 –/~185 million DSI-1170 ds540.0, ds540.1 Parker et al. (2004),
Woodruff et al. (1998, 2005),
Worley et al. (2005)
0104 ICOADS Release 2.4 Global Marine Surface Observations 1784–2007 –/~238 million DSI-1170 ds540.0, ds540.1 Parker et al. (2004),
Woodruff et al. (1998, 2005),
Worley et al. (2005)
0105 ICOADS Release 2.5 Global Marine Surface Observations 1784–2007 –/~261 million DSI-1173 ds540.0, ds540.1 Woodruff et al. (2011)
0200 ICOADS Auxiliary Kobe Global Marine Surface Observations 1889–1943 –/3135 ds530.0
0300 ICOADS Auxiliary Whaling Global Marine Surface Observations 1950–1984 –/20 ds530.0
0400 ICOADS Auxiliary Russian Global Marine Surface Observations 1950–2000 –/1789 ds530.0
0500 ICOADS Auxiliary Russian Global Marine Surface Observations 1889–2000 –/7873 ds530.0
0700 ICOADS Auxiliary Challenger Global Marine Surface Observations 1872–1876 (n/a) ds530.0
1000 Federal Climate Complex
Integrated Surface Database
Global Land Surface Observations 1901–2008 23 363/~1.2 billion DSI-3505 ds463.3 Smith et al. (2011)
1002 CDMP SAO/1001 Forms US Land Surface Observations 1928–1948 27/236 886 DSI-3851 Dupigny-Giroux et al. (2007)
1003 Russian Empire Stations Russian Land Surface Observations 1849–2000 1860/87 795 180 DSI-9290c
1004 Air Weather Service TD13 Global Land Surface Observations 1901–1973 32/55 748 ds467.0
1005 Hadley Centre Individual Stations from
Hadley Centre
1833–present 11/520 594 Allan et al. (2011)
1006 CDMP-International Chile, Mexico, Uruguay 1800s–1980 14/326 175 Dupigny-Giroux et al. (2007)
1007 READER Antarctic & Southern
Hemisphere
20 Stations via British
Antarctic Survey
1947–2007 18/562 784
1010 U.S. Air Force DATSAV US Air Force Compilation 1976–1980 DSI-9685 ds463.0
1011 Royal Netherlands Meteorological
Institute (KNMI)
KNMI stations 1911–2006 3/1 045 250
1012 CDMP Forts US Army Signal Service and
other 19
th
Century
Voluntary Observations
1841–1893 49/629 491 DSI-3297 Dupigny-Giroux et al. (2007)
2000 NCEP-NCAR BUFR Archive Global Observations 1948–2003 6625/26 225 199 ds090.0 Kalnay et al. (1996),
Kistler et al. (2001)
2001 NCEP Operational BUFR Archive Global Observations 1928–1948,
2003–2005
1053/2 940 516 ds090.0
3002 WASA Stations Observations
Sea Level Pressure
Northern Europe, Greenland 1871–1996 20/2 181 628 Schmith et al. (1997, 1998)
3004 Environmental Canada
Pressure Observations
Canadian Stations 1842–2004 746/25 277 856
3005 West African Synoptic observations West African Land Surface 1850–1980 123/3 022 702
3006 The Australian Bureau of
Meteorology Station
Pressure Dataset
Australian Land stations 1900–1956 63/1 418 093
(continued)
34 T. A. Cram et al.
ª2015 The Authors.
Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd.Geoscience Data Journal 2:31–46 (2015)
Table 2. (continued)
ISPD ID Name Description Period No. stations/records
NCDC
reference NCAR reference Reference publication
3007 Northern Italian Pressure
Observations
1878–1940 1/62 253 Maugeri et al. (2004, 2008)
3008 Brazil Surface Observations 1951–1980 8/78 ds486.0
3009 Spanish Hourly Pressure
Observations from EMULATE
Hourly Spanish Land Stations 1850–2003 5/190 899 Ansell et al. (2006)
3010 Germany Deutscher Wetterdienst (DWD)
Web Archive
1876–2000 9/405 167
3011 Austria Emulate Stations 1872–2002 9/467 124 Ansell et al. (2006)
3012 Switzerland Emulate Stations 1900–1973 8/815 363 Ansell et al. (2006)
3013 South Africa South African Weather
Service Stations
1850–2003 187/2 636 479
3014 Norway 1863–2007 16/225 687
3015 Croatia Meteorological
and Hydrological
Service Land Stations
Land Stations 1858–2005 4/444 398
3016 Portugal Portuguese SIGN stations 1860–2006 2/151 989 Valente et al. (2008)
4000 Hong Kong Hourly
Pressure Observations
Hong Kong Observatory 1885–1939 1/430 920
4001 Jakarta/Batavia
Pressure Observations
Dutch Royal Observatory 1866–1944 1/604 518 ds490.0
4002 Liverpool Proudman Ocean. Lab stations 1768–1793 1/9094
4003 Jersey Channel Island Pressure
Observations
Channel Island Stations 1864–1913 7/159 781
4004 CMDP-USNO US Naval Observatory
at Washington
1841–1913 1/83 261 Dupigny-Giroux et al. (2007)
5000 Antarctic Expedition keyed
by Hadley Centre
1899–1941 11/119 991 Allan et al. (2011)
5002 Byrd Antarctic Expeditions
Observations
Monthly Weather Review
Supplemental No. 41
1929–1930
8000 Atlantic/North Eastern Pacific
Hurricane Reanalysis
US Hurricane Re–Analysis Dataset 1848–present
8001 International Best Track Archive for
Climate Stewardship (IBTrACS)
National Climatic Data Center 1848–present DSI-9637 Knapp et al. (2010)
010000–019999 NCAR Upper Air Stations National Center for
Atmospheric Research
1943–1998 1081/1 275 272 ds370.1
The columns denote, respectively, the ISPDv2 collection ID, collection name, description, yearly period of record, total number of stations and observational records in the collection, reference
number for the corresponding National Climatic Data Center (NCDC) dataset, reference number for the corresponding dataset archived in the Research Data Archive (RDA) at the National Center
for Atmospheric Research (NCAR), and reference publication.
*The Air Weather Service TD13 observational records originating from collection ID 1004 are incorrectly labeled with collection ID 2001 in the native HDF5 tables in both ISPDv2 and ISPD ver-
sion 3.
The international surface pressure databank 35
ª2015 The Authors.
Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd. Geoscience Data Journal 2:31–46 (2015)
1. Dataset content and coverage
The ISPDv2 dataset is stored in the Hierarchical Data
Format version 5 (HDF5: http://www.hdfgroup.org),
which allows for efficient archiving of large, complex
data structures and a diverse set of metadata. Each
HDF5 file contains 13 tables and 15 directory subgroups
that define how to decode the individual records, and
each observation record includes metadata defining the
data collection source and observation type (e.g. sta-
tion observation, marine observation, surface pressure
observation from a radiosonde sounding).
Because the ISPDv2 was assimilated as observa-
tional input into the 20CR, each record also includes
the 20CR quality control and assimilation feedback
metadata. These quality control and feedback meta-
data include the results of the five-step quality control
procedure described in Appendix B of Compo et al.
(2011) and all the relevant statistical quantities
returned by the 20CR ensemble data assimilation sys-
tem. The format of the HDF5 metadata, therefore, is
designed to allow traceability of observations from
their original source to the ISPDv2, and to permit
direct feedback from the 20CR data assimilation back
to the original source archives.
Each observation at any single observation time is
assigned a unique number that when combined with
the time stamp (year, month, date, hour, and minute)
forms a unique identifier within the complete dataset.
Thus, every observation has an unambiguous refer-
ence within the full ISPDv2 dataset, which allows for
precise identification and traceability. This data man-
agement feature is critical for accurately adding addi-
tional metadata from other future reanalyses, and
evolving the ISPDv2 to new versions while maintaining
the usage provenance of each record.
The 20CR required hourly files from the ISPDv2 data
for the data assimilation system, thus each data file in
the ISPDv2 collection contains one hour of global obser-
vations. Based on this file organization and data cover-
age, a maximum of 24 data files per day and 8760 data
files per (non-leap) year exist in the ISPDv2 collection.
The total dataset volume is 491.32 GB. The HDF5 data
are available for download as either individual hourly
data files, or as yearly tar files, which are tarballs of one
entire year of HDF5 data files.
The ISPDv2 is also available in NetCDF and ASCII col-
umn data formats, both of which are derived from the
native HDF5 format. The data content within these two
formats is not a complete reproduction of the tabular
table content and metadata that are contained within
the HDF5 data. It does contain, however, essential
information, including the 20CR quality control feed-
back information, for most users to carry out their
research projects. The ASCII data are available as
monthly tar files for direct download from the National
Center for Atmospheric Research (NCAR) Research
Data Archive (RDA) website (http://dx.doi.org/
10.5065/D6SQ8XDW), while the NetCDF data are pro-
duced on demand through the data subsetting service
described in Section 3.1.
The data availability varies considerably over the
period of record. Maps of annual land station distribu-
tion (Figure 1) highlight the steady growth in the
number of reporting stations, and hence data cover-
age, since the year 1850 (station coverage maps for
every year are available at http://www.esrl.noaa.gov/
psd/data/ISPD/v2.0/). The sources of land station
Figure 1. Annual distribution of ISPDv2 land station locations for the years 1850, 1900, 1950, and 2000. Station coverage maps
for every year in the ISPDv2 are available at http://www.esrl.noaa.gov/psd/data/ISPD/v2.0/.
36 T. A. Cram et al.
ª2015 The Authors.
Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd.Geoscience Data Journal 2:31–46 (2015)
observations in the 19th and early 20th centuries are
located primarily in Europe and North America. The
data coverage increases dramatically across most of
the rest of the globe from 1950 to the present.
Figure 2 shows time series of the total number of
land observing stations in each indicated continental
region by year from 1850 to 2010. The notable decline
in stations during the mid-1960s –primarily in the
Asia/Eastern Europe time series –is attributed to the
reduction in the Integrated Surface Database records
during this period, and is explained in Smith et al.
(2011) as the result of the transition from keying of
observational data to digital transmission and receipt
of data.
The Asia time series also exhibits a considerable
decline in station coverage starting in the mid-1980s.
A listing of the number of stations originating from the
Integrated Surface Database for the years 1963–1964
and selected years between 1980 and 2001 is shown
in Table 3, which reveals these reductions are primar-
ily associated with the observations originating from
the Russian Federation and other former Soviet Union
countries. These reductions can be explained by the
deterioration of funding of the meteorological observa-
tion network in the final years of the Soviet Union
existence and thereafter in the 1990s and 2000s. The
observation network health during this post-Soviet
period was a function of the economic situation in
each of the 15 newly independent nations (and, to
some extent, a function of foreign sponsorship). The
China, North and Central America, and South-West
Pacific regions also exhibit notable decreases between
1963 and 1964.
The average number of pressure observations per
day contained in the 20CR feedback records from all
ISPDv2 components (station, marine, and tropical
cyclone) is illustrated by maps for the years 1900,
1950, and 2000 in Figure 3. The preponderance of
observations in the Northern Hemisphere in earlier
years is evident, as is the growth of marine observa-
tions over time (see Woodruff et al., 2011 for a com-
plete description).
The total number of observations per year in the
ISPDv2 increases steadily from approximately 100 000
records in 1870 to 53 million in 2010 (Figure 4). A
local increase and subsequent decrease in this trend
during the 1878–1894 period is attributed to the addi-
tion of 1.8 million records from the US Marine Meteo-
rological Journals and digitized for ICOADS Release
2.5 (Woodruff et al., 2011). A decrease during the
World War I years is evident, while an increase during
the World War II years is attributed to the inclusion of
1.6 million ICOADS records digitized from the UK
Royal Navy Ships’logbooks (Brohan et al., 2009;
Woodruff et al., 2011). A decrease during the mid–
1960s is associated with the aforementioned decline in
station records in the Integrated Surface Database
(Smith et al., 2011). A decrease in 2007 is most likely
due to a delay in processing, and therefore incomplete
records, in the Integrated Surface Database. Other
small-scale variations in the curve likely can be corre-
lated with increased scientific interest (local peaks)
and research budget reductions (local troughs; Flem-
ing, 2000).
The dataset contains reports from more than
10 000 land stations, which, in addition to the marine
observing systems reports, comprise over 1.5 billion
observations in total. Between 1860 and 1917, the
total number of marine and surface station observa-
tions is comparable, but in later years the total count
Figure 2. Time series of the total number of ISPDv2 land observing stations in each indicated continental region by year from
1850 to 2010. The inset panel indicates the boundaries used for the continental regions.
The international surface pressure databank 37
ª2015 The Authors.
Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd. Geoscience Data Journal 2:31–46 (2015)
is dominated by land surface station reports (not
shown). This prevalence of land station observations is
primarily due to the input data compiled for the
National Centers for Environmental Prediction (NCEP)/
NCAR Reanalysis project (1948–2003; Kalnay et al.,
1996; Kistler et al., 2001).
2. Data usage and application
2.1. Reanalysis
The primary motivation for the creation and develop-
ment of the ISPD was to facilitate progress on research
and understanding of long-term trends and variations
in global surface pressure. In particular, a long-term
historical dataset, such as the ISPD, becomes essential
to providing an observational underpinning to retro-
spective climate analysis datasets, commonly known as
reanalyses. Reanalysis products are used extensively in
climate research, applications, and services, including
for monitoring and comparing current climate condi-
Table 3. Total number of stations originating from the Integrated Surface Database and included in ISPDv2 for selected years
between 1963 and 2001.
WMO region 1963 1964 1980 1990 1993 1995 1998 2001
0 47 28 877 1007 925 927 869 1058
1 184 166 717 813 740 748 777 935
2 914 223 800 695 683 577 410 482
3 795 124 1031 878 835 751 607 584
4 466 353 916 932 864 876 867 1049
5 518 347 727 598 592 587 558 638
6 211 222 689 768 758 776 825 887
7 484 280 1524 1594 1671 1697 1560 1770
8 132 132 550 695 661 684 630 671
9 689 626 578 865 874 898 860 841
The columns represent the station count for the years listed and organized by WMO regional block number (0 and 1 =Europe; 2 and
3=Russian Federation and other former Soviet Union countries; 4 =Asia; 5 =China; 6 =Africa; 7 =North America, Central America, and
the Caribbean; 8 =South America and Antarctica; and 9 =South-West Pacific).
Figure 3. Maps showing the average number of pressure
observations per day contained in the 20CRv2 feedback
records from all ISPDv2 components: station, marine, and
tropical cyclone for the years 1900 (top), 1950 (middle), and
2000 (bottom). Counts of observations are made in five-de-
gree grid boxes.
Figure 4. Time series of the number of pressure observa-
tions per year in version 2 of the International Surface Pres-
sure Databank (ISPDv2) from 1870 to 2010. Note the
logarithmic scale along the y-axis. Inset panel: time series
during the same period showing the number of observations
in the Northern Hemisphere (blue curve) and Southern
Hemisphere (red curve).
38 T. A. Cram et al.
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Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd.Geoscience Data Journal 2:31–46 (2015)
tions with those of the past, identifying the causes of
climate variations and change, and preparing climate
predictions. Information derived from reanalyses is also
being used increasingly in commercial and business
applications in sectors such as energy, agriculture,
water resources, and insurance.
Prior to completion of the ISPD, most reanalysis
products (including those from the NCEP/NCAR Reanal-
ysis Project (Kalnay et al., 1996; Kistler et al., 2001)
and the European Centre for Medium-Range Weather
Forecasts [ECMWF; Uppala et al., 2005]) could only
extend back to about 1950 since they relied on assimi-
lating a set of observations that included upper-level
atmospheric information. The primary input data source
for the NCEP/NCAR Reanalysis, for example, are the
global rawinsonde observations, which contain a period
of record substantial enough to produce that reanalysis
back to 1948. The limited time range of these reanaly-
ses restricts their usefulness for many climate research
applications. The ISPD adds value by providing a much
longer period of record and thus enables the develop-
ment of reanalyses with longer time spans.
The first reanalysis to make use of the ISPD is the
20CR Project (Compo et al., 2011), which assimilates
only the ISPDv2 surface and sea-level pressure
observations and prescribes observed monthly sea–
surface temperature and sea–ice distributions from
HadISST1.1 (Rayner et al., 2003) as boundary condi-
tions. This global reanalysis dataset spans the late
19th century, the entire 20th century, and the early
21st century (1871–2012). It estimates the state of
the atmosphere –the ‘analysis’–by combining the
hourly and synoptic ISPDv2 observations in a 6-h time
window with a dynamically generated 9-h first guess
forecast initialized from the previous analysis. Cycling
this procedure with overlapping 6-h analyses and 9-h
forecasts has the effect of spreading the observational
information from the ISPD three-dimensionally in
space and in time.
As the 20CR was produced, the early period ISPDv2
‘beta’version was revised to include newly digitized
additions and improve the overall coverage of stations.
As ICOADS Release 2.5 was then available, it was also
included to increase the number of marine observa-
tions in the early period. Similarly for IBTrACS, newly
digitized records from the most recent versions of
IBTrACS were added to ISPDv2 as it evolved and
improved over time. The final ISPDv2, therefore, con-
tains multiple source versions of ICOADS and IBTrACS.
The newer versions of ICOADS and IBTrACS did not
change appreciably except to expand their data inputs
and coverage, therefore we do not anticipate that the
use of multiple versions introduces inconsistencies in
the pressure dataset.
2.2. Twentieth century reanalysis quality
control and data assimilation feedback
During the data assimilation processing of the 20CR,
the ISPDv2 input data were interrogated by a five-step
quality control procedure that included, among other
steps, checking the observations for meteorological
plausibility, comparing them with neighbouring data
values, and performing a bias correction on the land
component (see Compo et al., 2011 for more informa-
tion on this procedure). The 20CR then applied an
Ensemble Kalman Filter data assimilation method
which used background first-guess fields supplied by
an ensemble of 56 forecasts from an experimental
version of the NCEP Global Forecast System (GFS)
numerical weather prediction model (Kanamitsu et al.,
1991; Moorthi et al., 2001; Saha et al., 2006). These
quality control and data assimilation results, which
include the first-guess fields, analysis departures, bias
estimates, and observation errors, were then written
back into the ISPDv2 so that each observational
record contains this feedback information. Future
users of the ISPDv2, and those who contributed the
original observational data, therefore can utilize this
information to make an informed decision on the qual-
ity and usefulness of each observational record during
the 20CR time period.
One project that utilized the 20CR feedback meta-
data is the ERA-20C reanalysis (Poli et al., 2013),
which is the first reanalysis produced under the Euro-
pean Reanalysis of Global Climate Observations data-
base project (ERA-CLIM: www.era-clim.eu). The ERA-
20C is a global reanalysis that spans the 20th cen-
tury (1900–2010) assimilating only surface and sea-
level pressure observations from ISPD and ICOADS
and marine surface winds from ICOADS. Feedback
information from the 20CR was used in the bias cor-
rection scheme for ISPD data that were assimilated
in the ERA-20C reanalysis; this was based on a
break-point analysis using the 20CR first-guess depar-
tures (Hersbach et al., 2015). In locations where
breakpoints were suspected (e.g. instances of instru-
ment errors or a change in station location), the
ERA-20C bias correction scheme assigned less confi-
dence to the 20CR first-guess value, and thus was
allowed to be more adaptive compared to cases
where no irregularities in long-term departures were
identified.
In another study, Wang et al. (2014) used the
20CR feedback metadata to show that the strong
extratropical cyclone events in the 20CR agree well
with the geostrophic wind extremes derived from
in situ pressure observations. This study illustrates
how the 20CR quality control procedure performed
well in identifying errors in the observational record.
For example, the 20CR quality control system identi-
fied and rejected 143 of 146 erroneous observation
values from the Aberdeen, Scotland records for the
period 1871–1921. This quality control feedback infor-
mation, therefore, is valuable in identifying observa-
tion errors which might otherwise be overlooked and,
coupled with continued data rescue efforts such as
those facilitated by ACRE (Allan et al., 2011), serves
to strengthen and reduce uncertainty in the observa-
tional record.
The international surface pressure databank 39
ª2015 The Authors.
Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd. Geoscience Data Journal 2:31–46 (2015)
3. Data access and user services
3.1. Research data archive data location
and accessibility
The primary repository for ISPDv2 is in the RDA
(http://rda.ucar.edu) at NCAR in Boulder, Colorado.
The RDA is a free and open data collection where data
discovery can be achieved through faceted searches
based on Global Change Master Directory (GCMD:
http://gcmd.nasa.gov) metadata keywords, free text
queries, and lists highlighting the most used datasets.
Data access is free, but requires each user to register
through a simple online process that validates the sub-
mitted email address.
The ISPDv2 data access is organized by year and
month on the RDA website (http://dx.doi.org/
10.5065/D6SQ8XDW), and users may browse through
the pages to locate specific data of interest. Data files
are organized in default groups by observation year
and month. They can be downloaded directly from the
RDA web interface using server-supplied ‘wget’scripts.
Users may select a collection of files to download from
default lists by using the ‘Web File Listing’option
under the ‘Data Access’tab.
A more refined option is provided through the data
subset request form, which may be accessed via the
‘Get a subset’link under the ‘Data Access’tab. This
produces a customized data subset of the HDF5 data
based on user-provided constraints. Users can specify
the temporal limits, spatial domain, observation type
(s), and ASCII or NetCDF data output formats through
the data subset request form (Figure 5). The output
file compression can also be requested on this form
(not shown). Observations from individual observing
stations may also be requested, which is a useful fea-
ture for users who wish to procure time series for
specific locations or regions. Once submitted, the data
subset requests are produced by a delayed mode data
processing procedure. Users are notified and directed
to a web download location when their data request
output files are accessible.
3.2. Dataset citation
The RDA also provides a data citation service. The
dataset homepage provides citation syntax in the stan-
dard forms recommended by the Federation of Earth
System Information Partners (ESIP), American Meteo-
rological Society (AMS), American Geophysical Union
(AGU), DataCite, and the Geoscience Data Journal.
This dataset citation is also available in Research
Information System (RIS) format so that users may
import the citation for this dataset directly into their
citation reference management software (e.g. End-
Note, Zotero, etc.). One key element in the dataset
citation is the data access date (‘Accessed dd mmm
yyyy’). Leveraging the fact that RDA data users are
registered, a customized data citation can be prepared
for the user by using the ‘Get a customized data cita-
tion’link on the dataset home page. The dates that
users access the data are recorded and can be
retrieved on demand at later times.
3.3. File content metadata
File content metadata are collected as part of the data
processing and preparation of the ISPDv2 for the
RDA. The metadata supports additional information
services for interested users. The overall ISPDv2 meta-
data summary is provided from the dataset home
page under the ‘More Details’link. Here, tabulations of
the observing station location, observation type, plat-
form identification, and maps of the global distribution
for the full ISPDv2 can be viewed (Figure 6).
In addition, users may view the content metadata
for the yearly tar file archives by clicking on a looking
glass icon adjacent to the tar file listing, accessible
under the ‘Data Access’tab. This service enables users
to query the ISPDv2 via an interactive map of land
station locations, and more efficiently determine the
observational data available at any particular time and
region of interest (Figure 7).
3.4. Supporting software and documentation
Source code developed at the University of Colorado
CIRES and NOAA Earth System Research Laboratory
and written in C language to read and decode the
HDF5 data into ASCII column output is provided on the
RDA website under the ‘Software’tab on the dataset
home page. Documentation describing the HDF5 tables
and ASCII output is also available for download under
the ‘Documentation’tab on the dataset home page.
3.5. ECMWF data location and accessibility
A subset of the ISPDv2 is also archived at ECMWF
(http://apps.ecmwf.int/datasets). Here, users may
extract temporal subsets from the ISPDv2 archive
stored at ECMWF and refine their selection by obser-
vation platform. The output from these requests is
written in ASCII column format and contains the date,
location, observed value, report type, unique identifier
which allows traceability to other ISPD versions, and
several feedback parameters from the 20CR, including
the 20CR bias estimate, the 20CR ensemble mean first
guess pressure minus the ‘modified’observed pres-
sure, and the ensemble mean analysis pressure minus
the ‘modified’observed pressure. The ‘modified’pres-
sure is the pressure value after the 20CR system
adjusted it to be consistent with the orography in the
assimilating model. This is similar to a reduction to sea
level but instead is an adjustment to the 20CR orogra-
phy, which could be higher or lower than the station
elevation. In addition to the ASCII output, users may
produce observation count maps for their data selec-
tion on the ECMWF web interface.
40 T. A. Cram et al.
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Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd.Geoscience Data Journal 2:31–46 (2015)
4. Future plans
Since the release of ISPDv2, over 22 additional organi-
zations have contributed to the station and marine
components of the ISPD (Table 1) and the period of
record now extends back to 1755. These new contri-
butions have been incorporated into a newer version 3
of the ISPD (ISPDv3), which will be made available in
the near future through the NCAR RDA. The observa-
tion feedback archive (OFA) version of this dataset as
used in the ERA-20C reanalysis is available from
ECMWF (Hersbach et al., 2015).
The gain in observations for ISPDv3 is illustrated by
the time series shown in Figure 8. Most of the
increase occurs in the Northern Hemisphere, and there
are visible increases in the late 19th century and dur-
ing the World War I years. The 2007 decrease in
merged records from the Integrated Surface Database
into ISPDv2 (cf. Figure 4) is recovered in ISPDv3.
These and increases in other years come from diverse
station and marine collections contributed to the ISPD
under the auspices of GCOS, WCRP, and the ACRE ini-
tiative. This includes the initial efforts of the Old-
Weather.org citizen science project that focused on UK
Figure 5. The data subsetting interface found on the ISPDv2 Research Data Archive webpage after user authentication. Users
choose temporal range, spatial selection (choices are interactive map functions, manual latitude/longitude entry, or station identi-
fier entry), and also can select one or many observation types, and ASCII or NetCDF output data formats.
The international surface pressure databank 41
ª2015 The Authors.
Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd. Geoscience Data Journal 2:31–46 (2015)
Royal Navy observations during 1914–1923, the citi-
zen-led Todd Project team (http://www.charlestodd.-
net) that focused on recovering observations
assembled by Sir Charles Todd, Meteorologist of the
Colony of South Australia during 1879–1909, and the
efforts of many other university, national, and interna-
tional organizations (Table 1). Another notable contri-
bution are the North African locations, which arose
from the joint effort between the European Union-
funded EUropean Reanalysis and Observations for
Monitoring (EURO4M: http://www.euro4m.eu) project
in connection with the WMO/MEditerranean climate
DAta REscue (MEDARE) initiative (http://www.omm.
urv.cat/MEDARE; Brunet et al., 2014). The merging of
these contributions results in increases that are partic-
ularly dramatic when viewed as a map, as shown for
the example year of 1918 (Figure 9). The increases
over eastern South America, eastern Africa, China,
New Zealand, and selected central Pacific islands are
especially evident.
ISPDv3 (specifically, version 3.2.6) was imple-
mented into the European Reanalysis of Global Climate
Observations database (ERA-CLIM: www.era-clim.eu),
with a goal of using these and additional observations
Figure 6. Example of the content metadata interface found on the ISPDv2 Research Data Archive webpage. Here, users can
view and investigate tabulations of the location, observation type, platform identification, and maps of the global distribution of
observations for the full dataset.
42 T. A. Cram et al.
ª2015 The Authors.
Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd.Geoscience Data Journal 2:31–46 (2015)
in an ECMWF data assimilation system to generate
new global climate reanalyses of the 20th century.
The ERA-20C global reanalysis, the first reanalysis
under this project, spans the 20th century (1900–
2010) assimilating only surface and sea-level pressure
observations from ISPDv3 and marine wind observa-
tions from ICOADS 2.5 using a 4D-Var assimilation
system (Poli et al., 2013).
In addition, ISPD version 3.2.9 is being assimilated
into the next generation of the 20CR (version 2c).
20CRv2c uses the same NCEP atmosphere/land cou-
pled model at the same spectral resolution of total
wavenumber 62 (about 200 km by 200 km) as
20CRv2 but has different prescribed boundary condi-
tions. Daily sea surface temperatures come from a
new Simple Ocean Data Assimilation with sparse input
version 2 (SODAsi.2, B.S. Giese, H.F. Seidel, G.P.
Compo and P.D. Sardeshmukh, in review). Prescribed
monthly averaged sea ice concentrations from the
new COBE-SST2 (Hirahara et al., 2014) correct the
known misspecification in 20CRv2 (Compo et al.,
2011; Br€
onnimann et al., 2012). This activity is cur-
rently underway and will be reported on in due
course.
The ISPD also will be used in the planned centennial
coupled reanalysis being developed under the Japa-
Figure 7. Example of the file content metadata interface for the yearly tar files found on the ISPDv2 Research Data Archive
webpage. This service enables users to probe the ISPDv2 via an interactive map of land station locations, and more efficiently
search for the observational data at any particular time and region of interest.
The international surface pressure databank 43
ª2015 The Authors.
Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd. Geoscience Data Journal 2:31–46 (2015)
nese research project Program for Risk Information on
Climate Change (SOUSEI: http://www.jamstec.go.jp/
sousei/eng/research/theme_a.html), by the Meteoro-
logical Research Institute of the Japan Meteorological
Agency and collaborators (M. Ishii, 2014, pers. comm.).
Comments and questions on the ISPD can be direc-
ted to the RDA data specialist or left at the reanaly-
ses.org webpage for this dataset (http://reanalyses.org/
observations/international-surface-pressure-databank).
Acknowledgements
Construction of the ISPD is supported by the U.S.
Department of Energy Office of Science (Biological
and Environmental Research program) and the NOAA
Climate Program Office. The Twentieth Century
Reanalysis Project and the International Surface Pres-
sure Databank used resources of the National Energy
Research Scientific Computing Center and of the Oak
Ridge Leadership Computing Facility at Oak Ridge
National Laboratory, which are supported by the
Office of Science of the U.S. Department of Energy
under Contract No. DE-AC02-05CH11231 and Con-
tract No. DE-AC05-00OR22725, respectively. Manola
Brunet and Philip D. Jones are grateful to the Euro-
pean Union-funded projects EUropean Reanalysis and
Observations for Monitoring (EURO4M, FP7-SPACE-
2009-1 Project No. 242093) and Uncertainties in
Ensembles of Regional Reanalyses (UERRA, FP7-
SPACE-2013-1 Project No. 607193). Pavel Groisman
was partially supported by Grant 14.B25.31.0026 of
the Russian Ministry of Education and Science.
Renate Auchmann was supported by the Swiss
National Science Foundation (SNF; Project TWIST,
200021_146599/1).
The authors thank the following individuals and
organizations for their contributions: (1) Rajmund
Przybylak of the Nicolaus Copernicus University,
Department of Meteorology and Climatology, Poland.
(2) Frank Le Blancq and many others, Jersey Met Ser-
vice, for Channel Island data. (3) The IT group at
CIRES and NOAA/ESRL Physical Sciences Division. (4)
Prashant Sardeshmukh of University of Colorado/
CIRES for valuable guidance and input. (5) Paul Della-
Marta and MeteoSwiss colleagues who originally pro-
vided data to EMULATE. (6) Ingeborg Auer of Zen-
tralanstalt f€
ur Meteorologie und Geodynamik (ZAMG)
who originally provided Austrian data to EMULATE. (7)
Clive Wilkinson of NCDC and Climatic Research Unit,
University of East Anglia, Norwich, UK, and Eric Free-
man of NCDC for World War II UK Royal Navy Data.
(8) David Tse of Hong Kong Observatory for Hong
Kong data. (9) Volker Wagner for a subset of the
Deutscher Wetterdienst HISTOR marine data. (10)
Societ
a Meteorologica Italiana (SMI) for the Torino
record.
(11) Mac Benoy and the Australian Meteorological
Association, Todd Project team. (12) Dick Dee,
ECMWF, and the ERA-CLIM project. (13) Manuel Bar-
ros, Instituto Geof
ısico da Universidade do Porto,
University of Porto, Vila Nova de Gaia, Portugal. (14)
Jonathan Burroughs, Joseph Elms (retired) and Tho-
mas C. Peterson, NOAA National Climatic Data Center,
Asheville, NC, USA. (15) Karen Andsager (retired), for-
merly of Midwestern Regional Climate Center, Cham-
Figure 8. Time series of the number of pressure observa-
tions per year in version 2 (thin blue curve) and version
3.2.8 (red curve) of the International Surface Pressure Data-
bank (ISPD) from 1800 to 2011. Note the logarithmic scale
along the y-axis. Inset panel: Time series (shown on a linear
scale) during the period 1820 to 1920 showing the number
of observations in the Northern Hemisphere (blue curves)
and Southern Hemisphere (red curves). The shading high-
lights the gain in observations between the two versions.
Figure 9. Upper panel: Map showing the daily average
number of pressure observations in the new ISPDv3.2.8 for
the year 1918. Lower panel: Difference in the daily average
number of pressure observations between ISPDv3.2.8 and
the ISPDv2 (cf. Figure 3). Counts of observations are made
in five-degree grid boxes.
44 T. A. Cram et al.
ª2015 The Authors.
Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd.Geoscience Data Journal 2:31–46 (2015)
paign, IL USA. (16) Joelle Gergis, University of Mel-
bourne, Australia. (17) Jennifer Hardwick, Met Office
Hadley Centre, Exeter, UK. (18) David Jones and Blair
Trewin, Bureau of Meteorology, Melbourne, Victoria,
Australia. (19) Philip L. Woodworth, Proudman
Oceanographic Laboratory, Liverpool, UK. (20) Rein-
hard Zoellner, Deutscher Wetterdienst, Hamburg, Ger-
many. (21) Dr Birger Tinz, Division Maritime –
Climatological Monitoring Centre, Deutscher Wetterdi-
enst, Hamburg, Germany. (22) Ricardo M. Trigo, Insti-
tuto Dom Luiz, University of Lisbon, Lisbon, Portugal.
(23) Lu
ıs Filipe Nunes and Manuel Mendes, Instituto
Portugu^
es do Mar e da Atmosfera, Lisbon, Portugal.
(24) Scott D. Woodruff, NOAA Earth System Research
Laboratory, Physical Sciences Division, Boulder, CO,
USA. (25) Michael Kruk, ERT Inc., Asheville, NC, USA.
(26) Leslie Stoecker, Midwestern Regional Climate Cen-
ter, Champaign, IL, USA. (27) Hui Wan and Val Swail,
Environment Canada, Toronto, Canada. (28) Fatou
Sima, Division of Meteorology, Department of Water
Resources, Banjul, The Gambia. (29) Andrea Lock-
wood and Philip Mooney, Hollings Scholars, NOAA
Earth System Research Laboratory, Boulder, CO, USA.
(30) Sam Dean of National Institute of Water and
Atmospheric Research (NIWA), Auckland, New Zealand
for productive conversations.
The following persons affiliated with the University
of Giessen, Germany, digitized subdaily pressure data
originating from Europe, Asia, Africa, northern South
America, and the Caribbean: Christine Kolbe, Lisa Flen-
der, Marina Ostheimer, Johanna Englhardt, Athanasios
Tsikerdekis, Lamprini Dergianli, Despina Xoplaki, Chris-
tos Samaras, Eleni Kaimasidou, Nancy Gouta, Elisabet
Tsalkitzidou, Mary Athanasiou, Christakis Athana-
siou, Panagiota Katsaouni, Alexander Theocharis,
Stella Dafka, Kevin Pometti, Gail Kelly, Elda Fleitmann,
Lisa Theile, Petra Strehlau, Ines Stange, and Jonas
Viezens.
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