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Adjusted Monthly Precipitation, Snowfall and Rainfall for Canada (1874-1990)

Summary

NSIDC does not distribute this data set. Please contact the investigator or data compiler to acquire these data, and for further information about these data. Data Compiler: National Climatic Data Center.

This data set was distributed by NSIDC until October, 2003, when it was withdrawn from distribution because it duplicates the NOAA National Climatic Data Center (NCDC) data set TD-9816 'Canadian Monthly Precipitation' (Groisman, P.Y. 1998. National Climatic Data Center Data Documentation for TD-9816, Canadian Monthly Precipitation. National Climatic Data Center 151 Patton Ave., Asheville, NC. 21 pp.). TD-9816 contains monthly rainfall, snowfall and precipitation (the sum of rainfall and snowfall) values from 6,692 stations in Canada. NCDC investigator Pavel Groisman obtained the original data from the Canadian Atmospheric Environment Service (AES) in the early 1990s and adjusted the measurements to account for inconsistencies and changes in instrumentation over the period of record. TD-9816 contains both the original and adjusted data. Related data are the Historical Adjusted Climate Database for Canada, Version December 2002, and Rehabilitated Precipitation and Homogenized Temperature Data Sets provided by the Climate Monitoring and Data Interpretation Divisionís Climate Research Branch, Meteorological Service of Canada. Monthly Rehabilitated Precipitation and Homogenized Temperature Data Sets (updated annually) includes an alternative version of this data set using different correction methods. It is distributed by the Meteorological Service of Canada, who also provides a Microsoft Word document that compares the two different data correction methods.

Citation

Please contact the Data Compiler or Principal Investigator for information about how to cite this data set.

Table of Contents

1. Data Set Overview
2. Applications
3. Theory of Measurements
4. Acquisition Materials and Methods
5. Preparation and Description
6. Notes and Plans
7. Products and Access
8. References
9. Acronyms and Abbreviations
10. Document Information

1. Data Set Overview

Data Set Identification

Adjusted Monthly Precipitation, Snowfall and Rainfall for Canada (1874-1990)

Summary of Parameters

Discussion

This data set contains monthly rainfall, snowfall and precipitation from Canadian stations. The earliest records are from 1874, and the latest records are from 1990, although stations may have different starting and ending dates. Many researchers have used this data set in climatological assessments (including Groisman et al. 1993; Karl et al. 1993 a, b; Groisman and Easterling 1994, 1996; Groisman et al. 1994).

Efforts were made to minimize the effects of instrumental changes and other biases that complicate climatological analyses of Canadian precipitation (Goodison and Louie, 1986; Groisman and Easterling 1994; Metcalfe et al., 1997).

Related Data Sets

Former Soviet Union Monthly Precipitation Archive, 1891-1993

Monthly Rehabilitated Precipitation and Homogenized Temperature Data Sets (updated annually) includes an alternative version of this data set using different correction methods. It is distributed by the Meteorological Service of Canada, who also provides a Microsoft Word document that compares the two different data correction methods.

Investigator(s)

Investigator(s) Name and Title

Pavel Ya. Groisman
National Oceangraphic and Atmoshperic Agency
National Climatic Data Center
Federal Building
151 Patton Avenue
Asheville, NC 28801-5001

Mark Serreze
National Snow and Ice Data Center
449 UCB
University of Colorado
Boulder, CO 80309

Contact(s) Name, Address, Telephone, Fax, and e-mail

NSIDC User Services
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
Boulder, CO 80309-0449  USA
phone: +1 303.492.6199
fax: +1 303.492.2468
form: Contact NSIDC User Services
e-mail: nsidc@nsidc.org

2. Applications

This data set can be used to study precipitation patterns over Canada for investigations of climate variability and change. The precipitation data can also be used as input into hydrologic models and for validation of climate model output.

3. Theory of Measurements

Because snow gauges, rain gauges and snow rulers were used to take the measurements for this data set, this section is not applicable.

4. Acquisition Materials and Methods

Acquisition Equipment

Observations

Data Notes

These data were adjusted to improve temporal homogeneity by incorporating corrections for winds, wetting losses and inconsistencies related to different instrumentation.

5. Preparation and Description

Data Description

Spatial Coverage

Southernmost Latitude: 41N
Northernmost Latitude: 84N
Westernmost Longitude: 141W
Easternmost Longitude: 52W

Spatial Coverage Map

Temporal Characteristics

Temporal Coverage

The earliest records are from 1874, and the latest records are from 1990, although stations may have different starting and ending dates.

Data Characteristics

The precipitation data files are cdn_mon.pcp1, cdn_mon.rai1, and cdn_mon.sno1 (for precipitation, rainfall, and snowfall, respectively). Precipitation is the sum of rainfall and snowfall. Snowfall (measured as the depth of new snowfall) is converted into water equivalent using procedures described in Processing Steps. Data have been adjusted to account for errors due to winds, wetting losses and changes in gauge type. All files have the same structure and include (in addition to the station ID), coordinates, elevation and data flags (preserved from the original archive). Each of the three precipitation data files is approximately 13.5 MB in size. The canad_stn.lst file provides a listing of station names, positions and elevations, and is approximately 0.4 MB in size.

Table 1: Data Parameters for Precipitation Files (cdn_mon.pcp1 , cdn_mon.rai1, and cdn_mon.sno1)

Parameter (# of characters) Description Units Source Range
ID (A7) Station ID according to the Canadian AES classification Alphanumeric N/A N/A
ADJ (A1) Flag to indicate adjusted data. Will always be "A" N/A N/A N/A
LAT (F5.2) Station latitude (N) degrees and decimals N/A 41N to 84N
LON (F6.2) Station longitude (W) degrees and decimals N/A 52W to 141W
ELEV (I5) Station elevation tenths of meters N/A 0 to 2517 m
YEAR(I3) Year of the observation Year minus 1000 N/A 1874 to 1990
Array data(12) (I4) Contains 12 monthly totals of precipitation, rainfall, or snowfall (depending on file) tenths of mm

Rain gauge

Snow gauge

Or snow ruler

Minimum of zero
Array flg(12) (A1) Contains the data flags (DAT_flg(12)) from the original data set (AES archive) Alphanumeric

Rain gauge

Snow gauge

Or snow ruler

Blank

M

T

E

(see notes below)

Notes:


Table 2: Values for Array DAT_flg

Blank valid value (no comments)
M Missing value
T Precipitation trace(s) were reported during this month
E Original value in AES archive has been estimated

A line of data from any of the three data files can be read with the following FORTRAN statements:

character*7 id
character*1 adj, flg(12)
real lat, long, data (12)
integer elev, year

open (unit=10, name='cdn_mon.pcp1', status='old')

Read (10,100) id, adj, lat, lon, elev, year,
(precip(j), flg(j), j=1, 12)

100 FORMAT (A7, 1X, A1, 1X, F5.2, 1X, F6.2, 1X, I5, 1X, I3, 1X, 12 (1X, I4, A1))

Sample of Data Records (the first 10 lines from cdn_mon.pcp1)

   ID  ADJ LAT   LON    ELEV YEAR     one ARRAY DATA / ARRAY FLG combination for each of the 12 months 
1010066 A 48.87 123.28    39 984    -1M   -1M   -1M   -1M   -1M   -1M   34    46   330E  837E 2043E 1002E
1010066 A 48.87 123.28    39 985   235E   -1M  746   510   422   422    32    55   332  1344    -1M   -1M
1010066 A 48.87 123.28    39 986  1861E 1192   742E   -1M  591   212   289     0   342   328  1617   922E
1010066 A 48.87 123.28    39 987  1136E  528E  785   556E  491E   83    -1M   38    73   167    -1M 1403E
1010066 A 48.87 123.28    39 988   767   306E  924   538E  769   212   148E  344   607E  758  1648E   -1M
1010066 A 48.87 123.28    39 989  1050E  779E  933E   -1M  497E  318E  214E  414E   38   384  1089  1015E
1010066 A 48.87 123.28    39 990  1457E  621E   -1M  762E  524E   -1M   -1M  316    -1M   -1M 2319E 1832E
1010235 A 48.40 123.48   170 971    -1M   -1M   -1M   -1M   -1M  298E   58   113   517  1119  1732  2253 
1010235 A 48.40 123.48   170 972  2706  2117  1923   588    68   288   590   214   698   394   595  2919E
1010235 A 48.40 123.48   170 973  1393   386   360   270   228   275    75   141   172  1161    -1M 1597

The file canad_stn.lst is a listing of station names, positions, elevations and comments. File parameters are given in Table 3.

Table 3: Station File Parameters

ID1 (A7) Station identification
NAME (A28) Station name
LAT1 (F5.2) Station latitude in degrees and decimals (N)
LON1 (F6.2) Station longitude in degrees and decimals (W)
ELEV1 (I5) Station elevation in tenths of meters
COMMENT (A10) Additional information about the station name. See Groisman (1998).

NOTE: Missing values are shown as -9999 in ELEV1.

A line of data from file canad_stn.lst can be read with the following FORTRAN statements:

character*7 id1
character*28 name
character*10 comment
integer elev1
real lat1, lon1
open (unit=11, name='canad_stn.lst', status='old')
Read (11,100) id1, name, lat1, lon1, elev1, comment
100 FORMAT (A7,1X,A28,1X,F5.2,1X,F6.2,1X,I5,1X,A10)

Sample of Station Data Records

1010066 ACTIVE PASS             BC   48.87 123.28    39           
1010235 ALBERT HEAD             BC   48.40 123.48   170           
1010595 BAMBERTON OCEAN CEMENT  BC   48.58 123.52   853           
1010720 BEAR CREEK              BC   48.50 124.00  3507           
1010774 BEAVER LAKE             BC   48.50 123.35   609           
1010780 BECHER BAY              BC   48.33 123.63   121           
1010960 BRENTWOOD BAY 2         BC   48.60 123.47   381           
1010961 BRENTWOOD CLARKE ROAD   BC   48.57 123.45   304           
1010965 BRENTWOOD W SAANICH RD  BC   48.57 123.43   914           
1011467 CENTRAL SAANICH VEYANESSBC   48.58 123.42   533           
10114F6 CENTRAL SAANICH ISL VIEWBC   48.57 123.37   381           

Data Organization

Data Granularity

A general description of data granularity as it applies to the Earth Observing System Data and Information System (EOSDIS) appears in the EOSDIS Glossary.

The data set consists of four files. The maximum file size is 13.5 MB uncompressed; the minimum file size is 0.45 MB. The approximate total size of the files is 41 MB uncompressed.

Data Format

The data are in ASCII fixed text format.

Data Manipulations

All of the manipulations described in this section were performed at NOAA's National Climatic Data Center (NCDC). The Meteorological Service of Canada also provides an alternative version of this data set using different correction methods and a Microsoft Word document that compares the two different data correction methods.

Formulae

Derivation Techniques and Algorithms

The data were adjusted to improve temporal homogeneity by incorporating corrections for winds, wetting losses and inconsistencies related to different instrumentation. Details are provided by Groisman (1998). Adjustments are summarized under Data Processing Sequence.

Data Processing Sequence

Overview of biases in precipitation data

Wind-induced undercatch

Bruce and Clark (1966), in their Introduction to Hydrometeorology, cite studies from as early as 1884 showing that as wind speed increases, measured precipitation is reduced. This effect is much greater for snow than for rain. Gauges are usually shielded to reduce wind undercatchment, but wind effects are still the largest source of error in precipitation measurements. Groisman et al. (1991) note that undercatch can be as much as 50% of measured precipitation. Wind loss depends on gauge type (see for example Goodison et al. 1998), where the gauge is located relative to obstacles, how high the gauge is mounted, and the type of precipitation.

Trace precipitation amounts

Trace precipitation is precipitation in an amount too small to be resolved by the collecting gauge. For example, a measure on the Tretyakov gauge (used in Russia) of less than 0.1 mm is recorded as trace. Corrections for trace are usually made by adding in a set amount for each day on which trace precipitation was recorded. Trace precipitation can contribute a significant amount to monthly or annual precipitation totals in regions of little precipitation. For instance, Yang et al. (1999) found that the yearly correction for trace precipitation was 5%-11% of the gauge-measured annual precipitation for northern Greenland, but was a negligible 3% or less for southern Greenland where precipitation is much higher.

Wetting loss

Wetting loss occurs when a gauge is emptied into a measuring device to obtain a precipitation total. The small amount of precipitation that remains behind in the gauge (that is, sticking to its sides) is the wetting loss. The size of this loss depends on how often the gauge is emptied, as well as on the type of gauge and the type of precipitation. Yang et al. (1999) found that for Greenland, the wetting loss is 5-6% of gauge-measured annual precipitation for northern Greenland, and 2-3% for southern Greenland.

Evaporation loss

Evaporation loss is the amount of precipitation lost from the gauge by evaporation between measurements. It depends on gauge type, the frequency of measurements, and weather conditions. While evaporation can be significant (up to 0.8 mm per day at one Finnish site using the Tretyakov gauge), it is not generally possible to apply a general correction due to the site-specific nature of the loss (Yang et al. 1995).

Processing Steps

Rainfall Adjustments (cdn_mon.rai1)

Earlier studies (Metcalfe et al. 1997) indicate that before 1975, Canadian gauges had wetting losses of approximately 0.16 mm per measurement. It was also recommended that rainfall measurements be multiplied by 1.02 to account for wind-induced undercatch.

Information on the number of measurements per day (which would allow a systematic wetting correction) is not available at all stations. To provide for a more homogeneous time series, the wetting correction before 1975 made use of the mean number of days per month with rainfall at the site or, if not available, a value interpolated from nearby locations. The mean values are based on data from the early 1980s onwards, when total rainfall days began to be inserted in the original archive. A total of 2172 stations have the mean values information for at least five years.

The total monthly rainfall prior to 1975 was taken as the measured rainfall plus the mean number of days with rain multiplied by 0.2. This adjusted total was then multiplied by 1.02 to account for wind undercatch. Subsequent to 1975 and with the adoption of the improved Type-B gauge (Metcalfe et al. 1997), a wetting correction was not deemed necessary and the monthly rainfall was adjusted only for wind undercatch. These adjustments increase rainfall by approximately 5 percent before 1975 and 2 percent thereafter. There are no corrections for trace rainfall events. See Groisman (1998) for details.

Snowfall Adjustments (cdn_mon.sno1)

Two instruments are used in Canada to assess snowfall water equivalent. At 85 percent of stations, a snow ruler is used to measure the depth of freshly fallen snow, which is then converted into water equivalent using a 10:1 ratio. Starting from the early 1960s, some stations were equipped with Nipher-shielded elevated snow gauges that directly measure the water equivalent of snow (Groisman and Easterling, 1994). However, measurements from the Nipher guage are prone to wind-induced error. Errors appear to be on the order of 15 percent (Golubev et al., 1995), but Groisman (1998) notes that the errors will be site specific. While accurate corrections for gauge undercatch requires wind and site exposure information, this information was not available, requiring the use of climatological adjustments.

Climatological ratios (RAT) of monthly snow water equivalent between the Nipher gauge and the snow ruler (Nipher/ruler) were computed. RAT is generally less than 1.0, and in cold climates as low at 0.6. The RAT values were increased by a factor of 10/9 to account for an average snow undercatch by the Nipher gauge (that is, the undercatch is assumed to be systematic). The RAT values were then multiplied by the water equivalent as determined from the 10:1 conversion of the ruler measurements. This procedure adjusts the assumed snowfall density. The adjustments were only performed where the mean monthly snowfall exceeded 3 centimeters. For cases in which a RAT value could not be determined due to insufficient data, a value of 1.0 was assumed. Deriving the RAT values required identification of those sites and periods for which frozen precipitation was measured by the Nipher gauge. These procedures are outlined by Groisman (1998).

cdn_mon.pcp1

To obtain total precipitation, adjusted rainfall totals (from cdn_mon.rai1) and snowfall totals (from cdn_mon.sno1) were added together.

Adjustments for traces

While the need for trace adjustments is recognized, especially in Canada where a significant part of liquid water precipitation equivalent (greater than 10 percent) can be in the form of traces (Bradley and England 1978; Woo and Steer 1979; Metcalfe et al. 1997), the existing practice of reporting traces does not allow their introduction into the data. Figure 1 illustrates differences in how they were reported at the first order network in Canada during the 20th century. An attempt to use the reported traces and their treatment as non-zero amounts will definitely result in inhomogeneity of the precipitation time series. The researcher who needs less biased values of Canadian precipitation may consider introducing an additional climatological constant value to each data value (specific for season and location).


Figure 1. Changes with time in percent of days (per year) with reported trace precipitation at the Canadian first-order stations for rainfall and snowfall separately. The increase since 1945 reflects the switch from the British to metric system in the early 1970s and a significantly higher diligence in trace reporting after World War II. (Figure 1 is taken from Groisman, P.Y. 1998. National Climatic Data Center Data Documentation for TD-9816, Canadian Monthly Precipitation, pp. 21, National Climatic Data Center, 151 Patton Ave., Asheville, NC.)

Errors

Sources of Error

Please see Processing Steps and Future Modifications and Plans for information about errors.

6. Notes and Plans

Known Problems with the Data

Inhomogeneities may remain in the time series due to uncertainties in RAT values, inconsistencies in the reporting of trace precipitation and the simple nature of the adjustments. See Future Modifications and Plans.

Usage Guidance

Users of these data should be aware that precipitation and snowfall are notoriously difficult to measure. In particular, care should be exercised in any assessment of trends. See Processing Steps for more information.

Any Other Relevant Information about the Study

P. Groisman has also prepared a monthly precipitation data set for the Former Soviet Union. See Related Data Sets.

Future Modifications and Plans

Users who are not satisfied with any of the procedures used or who possess more elaborate information, may improve the data set by one of the methods listed below:

7. Products and Access

Data Center Identification

National Snow and Ice Data Center (NSIDC)

Procedures for Obtaining Data

NSIDC does not distribute this data set. Please contact the investigator or data compiler to acquire these data, and for further information about these data. Data Compiler: National Climatic Data Center

8.References

Recommended

Goodison, B.E. 1978. Accuracy of Canadian snow gauge measurements. Journal of Applied Meteorology 17:1542-1548.

Groisman, P.Ya., D.R. Easterling. 1994. Variability and trends of precipitation and snowfall over the United States and Canada. Journal of Climate 7:184-205.

Karl, T.R., Quayle, R.G., Groisman, P.Ya., 1993. Detecting climate variations and change: New challenges for observing and data management systems. Journal of Climate 6:1481-1494.

Metcalfe, J.R., B. Routledge, K. Devine. 1997. Rainfall measurement in Canada: Changing observational methods and archive adjustment procedures. Journal of Climate 10:92-101.

Related

Akima, H. 1978. A method of bivariate interpolation and smooth surface fitting for irregularly distributed data points. ACM Transactions on Mathematical Software 4:148-159.

Bradley, R.S., J. England Jr. 1978. Recent climatic fluctuations of the Canadian high Arctic and their significance for glaciology. Arctic Alpine Research 10:715-731.

Bruce, J.P., R.H. Clark. 1966. Introduction to Hydrometeorology, Permagon Press, Oxford. 319 pp.

Currie, B.W. 1947. Water content of snow in cold climates. Bulletin of the American Meteorological Society 28:150-151.

Ferguson, H.L., D.M. Pollock. 1971. Estimating snowpack accumulation for runoff prediction. Canadian Hydrology Symposium No.8: Runoff from Snow and Ice. Inland Water Branch, Dept. of Energy, Mines and Resources, Quebec City. 7-27.

Golubev, V.S., 1993. Experience of correction of precipitation point measurements and analysis of correction procedures. AMS Proceedings: Eighth Symposium on Meteorological Observations and Instrumentation Anaheim, CA. 325-328.

Golubev, V.S., V.V. Koknaeva, A.Yu. Simonenko. 1995. Results of atmospheric precipitation measurements by national standard gauges of Canada, USA, and Russia. Meteorologia i Gidrologia 2:102-110. (in Russian)

Goodison, B.E., H.L. Ferguson, G.A. McKay. 1981. Comparison of point snowfall measurement techniques. In: D.M.Gray and D.M. Male (Eds). "Handbook on Snow: Principles, processes, management and use." Pergamon Press. 200-210.

Goodison, B.E., P.Y.T. Louie. 1986. Canadian methods for precipitation measurement and correction. WMO/TD-No. 104. Instruments and observing methods. Report No. 25. Papers presented at the Workshop on the Correction of Precipitation Measurements, Zurich, Switzerland, 1-3 April, 1985. 141-145.

Goodison, B.E., J.R. Metcalfe. 1989. Canadian participation in the WMO Solid Precipitation Measurement Intercomparison: preliminary results. WMO/IAHS/ETH International Workshop on Precipitation Measurement, St.-Moritz, Switzerland, 3-7 December, 1989, 121-125.

Goodison, B.E., P.Y.T. Louie and D. Yang. 1998. WMO solid precipitation measurement intercomparison, final report. World Meteorological Organization, Geneva. 212 pp.

Groisman, P.Y., V.V. Koknaeva, T.A. Belokrylova, and T.R. Karl. 1991. Overcoming biases of precipitation measurement: A history of the USSR experience, Bulletin of the American Meteorological Society 72(11):1725-1733.

Groisman, P.Ya., R.W. Knight, T.R. Karl, R.R. Heim Jr. 1993. Inferences of the North American snowfall and snow cover with recent global temperature changes. Proceedings of "Snow Watch '92" Conference, Niagara-on-the-Lake, Canada, March 30 - April 1, 1992. 44-51.

Groisman, P.Ya., T.R. Karl, R.W. Knight, G.L. Stenchikov. 1994. Changes of snow cover, temperature, and radiative heat balance over the Northern Hemisphere. Journal of Climate 7:1633-1656.

Groisman, P.Ya., D.R. Easterling. 1996. Variability and trends of precipitation and snowfall over North America. In "Natural and Climate Variability on Decade-to-Century Time Scales," National Academy Press. 67-77.

Groisman, P.Ya., T.R. Karl, D.R. Easterling, R.W. Knight, P.B. Jamason, K J. Hennessy, R. Suppiah, Ch.M. Page, J. Wibig, K. Fortuniak, V.N. Razuvaev, A. Douglas, E. Forland, P.-M. Zhai. 1999. Changes in the probability of heavy precipitation: Important indicators of climatic change. Climatic Change 42 (1): 243-283.

Groisman, P.Y. 1998. National Climatic Data Center Data Documentation for TD-9816, Canadian Monthly Precipitation. National Climatic Data Center 151 Patton Ave., Asheville, NC. pp. 21.

Hare, F.K., 1980. Long-term annual surface heat and water balances over Canada and the United States south of 60°N: Reconciliation of precipitation, run-off and temperature fields. Atmosphere-Ocean No.18(2): 127-153.

Karl, T.R., P.Ya. Groisman, R.W. Knight, R.R. Heim Jr. 1993b. Recent variations of snow cover and snowfall in North America and their relation to precipitation and temperature variations. Journal of Climate 6:1327-1344.

Kurtyka, J.C., 1953. Precipitation Measurement Study. State of Illinois, Department of Registration and Education, State Water Survey Division , Urbana, Il. Report of Investigation # 20, 178 p.

Mekis, E., W.D. Hogg. 1997. Rehabilitation and analysis of Canadian daily precipitation time series. AMS Proceedings of the 10th conference on applied climatology in Reno, Nevada, October 20-23. American Meterology Society, Boston, Mass. 300-304.

Neff, E.L. 1977. How much rain does a rain gauge gauge? Journal of Hydrology 35:213-220.

Potter, J.G. 1965. Water content of freshly fallen snow. Department of Transport, Meteorological Branch. Cirular 4232, Technical 569. 12 p.

Sanderson, M. 1975. A comparison of Canadian and United States standard methods of measuring precipitation. Journal of Applied Meteorology 14:1197-1199.

Sevruk B. 1982. Methods of correction for systematic error in point precipitation measurement for operational use. WMO, Operational Hydrology Report Geneva. 21:91.

Woo, M.-K., P. Steer. 1979. Measurement of trace rainfall at a high arctic site. Arctic 32:80-84.

World Meteorological Organization (WMO). 1973. Annotated bibliography on precipitation measurement instruments. WMO Geneva, Switzerland 2E. 343:278 p.

World Meteorological Organization (WMO). 1979. Climatic Atlas of North and Central America, Vol. 1. WMO UNESCO Geneva, Switzerland. 39 p.

World Water Balance and Water Resources of the Earth. 1974. Gidrometeoizdat, Leningrad. (in Russian; published in English by UNESCO Press in 1978). 638 p.

Yang, D., B.E. Goodison, J.R. Metcalfe, V.S. Golubev, E. Elomaa, T. Gunther, R.E. Bates, T. Pangburn, C.L. Hanson, D. Emerson, V. Copaciu, J. Mikovic. 1995. Accuracy of Tretyakov Precipitation Gauge: Result of WMO Intercomparison, 52nd Eastern Snow Conference Toronto, Canada. 95-106.

Yang, D. 1999. An improved precipitation climatology for the Arctic Ocean. Geophysical Research Letters 26 (11):1625-1628.

Yang, D., S. Ishida, B.E. Goodison, T. Gunther. 1999. Bias correction of daily precipitation measurements for Greenland. Journal of Geophysical Research 104 (D6): 6171-6181.

9. Acronyms and Abbreviations

Acronyms and Abbreviations

The following acronyms and abbreviations are used in this document.

AES Atmospheric Environment Service
EOSDIS Earth Observing System Data and Information System
NCDC National Climatic Data Center
NSIDC National Snow and Ice Data Center
NOAA National Oceanic and Atmospheric Administration

10. Document Information

Document Revision Date

04 August 2000

Document Review Date

03 August 2000

Document Curator

NSIDC writers

Document URL

http://nsidc.org/data/docs/daac/nsidc0072_canadian_precip.gd.html