|
||||||
|
|
||||||
|
||||||
|
|
||||||
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This data set was distributed by NSIDC until October, 2003, when it was withdrawn from distribution because it duplicates the NOAA National Climatic Data Center (NCDC) data set TD-9816 'Canadian Monthly Precipitation' (Groisman, P.Y. 1998.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 Division’s 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.
Please contact the Data Compiler or Principal Investigator for information about how to cite this data set.
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
Adjusted Monthly Precipitation, Snowfall and Rainfall for Canada (1874-1990)
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).
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.
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
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
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.
Because snow gauges, rain gauges and snow rulers were used to take the measurements for this data set, this section is not applicable.
These data were adjusted to improve temporal homogeneity by incorporating corrections for winds, wetting losses and inconsistencies related to different instrumentation.
Southernmost Latitude: 41N
Northernmost Latitude: 84N
Westernmost Longitude: 141W
Easternmost Longitude: 52W
The earliest records are from 1874, and the latest records are from 1990, although stations may have different starting and ending dates.
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 |
|
Minimum of zero |
Array flg(12) (A1) |
Contains the data flags (DAT_flg(12)) from the original data set (AES archive) |
Alphanumeric
|
|
(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))
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)
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 |
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.
The data are in ASCII fixed text format.
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.
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.
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).
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.)
Please see Processing Steps and Future Modifications and Plans for information about errors.
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.
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.
P. Groisman has also prepared a monthly precipitation data set for the Former Soviet Union. See Related Data Sets.
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:
Acquire updates to the data. The 1990s are not covered by the present archive. Additional and more recent data will benefit climate change studies, and significantly improve the accuracy of the RAT estimates.
Acquire additional metadata.
As a last resort, the data values were used to retrieve the information about the period of Nipher snow gauge installation. This method is prone to errors due to random errors in precipitation/rainfall/snowfall data and could miss the date of the gauge installation in the months when the RAT is naturally close to 1. Therefore, a conservative approach was used in the RAT estimation which discarded many values that potentially could be useful. The user who has more information about the period of snow gauge installation at Canadian stations can produce better RAT estimates. (See Groisman, 1998).
Sometimes basic metadata such as coordinates and site elevation were incomplete. Several stations were discarded because of missing coordinate information, and the use of estimated coordinates for some others. Elevation at more than one hundred sites is missing.
Lacking wind data and descriptions of instrument exposure at the stations, it was not possible to account accurately for wind-induced biases in Nipher-shielded Canadian snow gauge measurements (Sevruk 1982; Goodison 1978). A scalar factor of 0.9 used throughout the entire country is a gross approximation of the average snow gauge catch. The user who has a better knowledge of the wind regime and site exposure at some of the 289 stations where RAT estimates are available, can significantly improve the time series of liquid water equivalent of snowfall around these stations.
Use of daily precipitation data for adjustments. Canadian specialists (Metcalfe et al. 1997; Mekis and Hogg 1997) argue that a much better adjusted monthly precipitation product can be generated using daily records and supplementary information (including wind over the gauge orifice, traces, and the number of non-zero precipitation measurements per month). However, most users do not have access to this supplementary information. Some of it is absent entirely (for example, wind speed, exposure description of the past instrument locations) or is of questionable quality (trace reports, see Figure 1). Future plans are to check the potential level of adjustment improvement that can be achieved using daily data from a selected subset of the best Canadian first order stations. (Figure 1 was generated from this subset.)
National Snow and Ice Data Center (NSIDC)
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
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.
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.
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 |
| WIST | Warehouse Inventory Search Tool |
04 August 2000
03 August 2000
NSIDC writers
http://nsidc.org/data/docs/daac/nsidc0072_canadian_precip.gd.html
