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Sustainable Society:  A society that balances the environment, other life forms, and human interactions over an indefinite time period.







Earlier in the Year Snowmelt Runoff and Increasing Dewpoints for Rivers in Minnesota, Wisconsin and North Dakota

Patrick J. Neuman, Snow Hydrologist

September 11, 2003


I.     Abstract
II.    Snowmelt physics
III.  Hydrologic area and data sources
IV.   Timing of annual snowmelt runoff
V.     Average monthly dewpoint
VI.   Conclusions on the timing of snowmelt runoff and humidity
VII.  Air temperatures
VIII. Additional discussion
IX.    Recommendations

X.     References
Links to Tables &  Figures

I.  Abstract

Daily river flow data were used to evaluate the timing of snowmelt runoff at three river stations within the Northern Great Plains and Upper Midwest.  Timing of snowmelt runoff is shown by a X-Y plot using 10 year moving averages for “Annual Beginning Day of Snowmelt Runoff” at the river stations for 1910-2003.  Average dewpoint plots are shown for three climate stations near the river stations.  The plots show monthly January ‑ April dewpoint for 10 year moving averages for 1948 to 2003.  A discussion of snowmelt physics is included, describing how humidity as measured by dewpoint affects the rate of snowmelt.  Based on the study results, shown by the plots on the timing of annual snowmelt runoff and by plots of dewpoint averages at climate stations, conclusions are reached, and recommendations are given.

II.  Snowmelt Physics

After a long period of cold weather, a snowpack can absorb large amounts of heat before thaw occurs.  Once the temperature of the snowpack reaches zero degrees Celsius throughout, liquid water starts forming within the snowpack.  When the liquid water exceeds a threshold (about 15 percent of total snowpack water equivalent), snowmelt begins.

Solar radiation is the dominant energy transfer for snowmelt during clear sky periods.  Usually snowmelt occurs on south facing slopes and hilltops before snowmelt occurs on north facing slopes and other parts of the basin.  In winter and early spring, sun angles are low and days are short; thus snowmelt from solar radiation alone during this period is usually gradual and intermittent.

The significance of latent heat for snowmelt has been described by Dunne and Leopold (1978):

“If water from moist air condenses on a snowpack, 590 calories of heat are released by each gram of condensate. This is enough energy to melt approximately 7.5 gm of ice, which when added to the condensate yields a total of 8.5 gm of potential runoff”.

Latent and sensible heat transfers can result in high snowmelt rates, as warm moist air moves into a region.  Latent and sensible heat transfers can cause rapid snowmelt from all parts of a basin simultaneously, day and night, even during winter.  Warm temperatures, high humidity, and strong winds have large effects on the rate of snowmelt.  In comparison, heat supplied by rainfall is usually minor, unless a warm rainfall of long duration occurs. A more detailed description of equations for snowmelt are given by Price and Dunne (1976).

Dunne and Leopold (1978) show that “highest melt rates were associated with the warm sector of a large weather disturbance” (Quebec, May of 1973).  For the last three days of an eight day melt of the snowpack in May of 1973 (Quebec), melt due to latent heat was shown to be nearly equal to melt from net radiation, and melt from latent heat during the last three days was shown to be around 50 percent of the melt due to sensible heat transfer from atmospheric convection (mixing).

From the theoretical and physical descriptions given above, it is clear that the rate of snowmelt increases as humidity increases, due to latent heat released as water vapor condenses when air temperatures are above freezing.

III.  Hydrologic Area and Data Sources

The National Weather Service (NWS) North Central River Forecast Center (NCRFC) is responsible for hydrologic forecasting for rivers in the Upper Midwest and parts of the Northern Great Plains.  NWS hydrologic models and NCRFC calibrated snow and soil moisture/runoff model parameters are used in forecasting snowmelt runoff flow into the rivers, lakes, and reservoirs (Neuman, 1999).

River stations selected for this study, which are within the headwaters of three of the major basins of North America, include:

Red River at Fargo, ND, headwaters to Hudson Bay
St. Louis River at Scanlon, MN, headwaters to Lake Superior
St. Croix R. at
St. Croix Falls, WI, headwaters to Mississippi River

The river stations were chosen based on:

1)  quality flow data from the early 1900s to current;
2)  annual snowmelt runoff nearly every year;
3)  location within the Upper Midwest and Northern Great Plains; and
4)  author's experience & expertise gained working in hydrology in
Midwest and Great Plains

Hydrologic characteristics of the river basins, terminology, and study methodology are outlined in Table 1 (work sheet for Figure 1, discussed below).

Source of mean daily flow data was the United States Geological Survey (USGS).  Source of dewpoint data was the Midwest Regional Climate Center database.

IV.  Timing of Annual Snowmelt Runoff

Mean daily flows were used in this study to determine “Annual Beginning Day of Snowmelt Runoff” for years from 1910 through 2003 at the three river stations.  The methodology is explained in Table 1 (work sheet for Figure 1).

Figure 1 shows 10 year moving averages for annual beginning day of snowmelt runoff at the river stations.  The 10 year moving averages for Julian Days (each Julian Day representing the beginning date of snowmelt runoff for a year at a river station) are plotted on the 10th year of the 10 year moving Julian Day averages.

The data on Figure 1 show trends for recent earlier in the year annual snowmelt runoff at the river stations, that began during the 1960-1980 period, and became more evident during 1981-2002 period.

V.  Average Monthly Dewpoint

Climate stations that are within or near the three river basins include:

Fargo, North Dakota (within Red River basin)
, Minnesota (southeast of St. Louis River basin)
Eau Claire
, Wisconsin (southeast of St. Croix River basin) 

Monthly January to April dewpoint (10 year moving averages), based on 1948‑2003 monthly averages, are shown in figures 2‑4. The figures show recent increasing dewpoint trends for January, February, and March 10 year moving averages, but no trends for April monthly dewpoints.

VI.  Conclusions on the Timing of Snowmelt Runoff and Humidity

1) Trends were shown for recent earlier in the year annual snowmelt runoff at three river stations within the Northern Great Plains and Upper Midwest.

2) Trends were shown for recent increasing dewpoint averages for January, February, and March but not April.

Other factors besides humidity are important in affecting snowmelt, including air temperatures, wind speeds, temperature of precipitation, ground temperatures, extent of snowpack over the entire Great Plains and Midwest and its albedo (characteristics of the snow cover in reflecting solar radiation).

VII.  Air Temperatures

Based on snowmelt physics, historical modeling, and real time operations involving snowmelt and snowmelt runoff, air temperatures and humidity are likely the most significant factors affecting the rate of snowmelt.

Thus some investigation and reporting on air temperatures is warranted with respect to snowmelt.  “The largest increases in both temperatures and humidity for the Northeast, Midwest, and Northern Great Plains have been during Winter and early Spring months” (Neuman, 2003).  The report by Neuman (2003) included selection of temperature stations and analysis and summaries of mean air temperature and dewpoint data for many stations in the Midwest and Northern Plains.  In an investigation and report on the climate in the Great Lakes region, from a study that was entirely independent from the work and report on the Northeast, Midwest, and Northern Great Plains by Neuman (2003), the Kling (2003) concluded for the Great Lakes region that:

“In the past four years, ..., annual average temperatures have ranged from 2 to 4º F (1 to 2º C ) warmer than the long-term average and up to 7 ºF (4º C) above average in winter.”

The conclusions on temperatures by Kling (2003) and Neuman (2003) were in agreement, even though the work was done independently.

VIII.  Additional Discussion

From the snowmelt physics discussion in Section II, it is clear that humidity and the rate of snowmelt are connected, with increases in humidity resulting in additional heat transfer from the latent heat of condensation as water vapor condenses on a snowpack of 0 degrees Celsius, when air temperatures are above freezing.  The process can be shown theoretically but would require considerable work to demonstrate experimentally or with operational hydrologic and meteorological data.  This work has shown the trend for earlier snowmelt runoff in recent years, and the trends for higher dewpoints in recent years, but this work has not proven that the higher average dewpoints have caused the earlier in the year recent annual snowmelt runoffs.

Mean daily flow records that were used in the evaluation of the timing of snowmelt runoff for the river stations in this study range from 1902 to current, a period of 105 years of record.  However, monthly dewpoint data for this study was only available from 1948 to current, only 55 years of record.  Although figures 2‑4 indicate trends for recent increasing monthly dewpoint averages for January, February, and March, the 55 years of record may be insufficient for making firm statements regarding long term trends in average dewpoints.

However the river flow data records, with 105 years of record, show the timing of annual snowmelt runoff for years that preceded the dewpoint records used in this study.  In other words, the river flow data used in the evaluation of the timing of annual snowmelt runoff for 1902 through 1947, infer the effects of temperatures and humidity for the period 1902 through 1947.

In viewing Figure 1, the 1920s to early 1950s period had earlier annual snowmelt runoffs than the late 1950s and 1960s period.  However, the period from the mid 1980s to the snowmelt runoff period in 2003 had the earliest annual snowmelt of record, substantially earlier than the 1920s to early 1950s period.  An evaluation of mean annual dewpoints at Minneapolis, MN from1918 to the 1940s, which were calculated from mean annual relative humidity and annual air temperature data (Table 2.) shows that 5 year annual dewpoint averages for 1998 through 2002 exceeded all previous 5 year averages at Minneapolis since the beginning of record for calculated annual dewpoint averages (1918).

IX.  Recommendations

The recent trends shown in this study for earlier annual snowmelt runoff at river stations within the Upper Midwest and Northern Great Plains, and for  increasing January - April dewpoint averages call for:

1)  Review of NWS hydrologic models used by NCRFC in modeling snowmelt runoff.

2)  Review of NCRFC snow and soil moisture model parameters used in models by NCRFC in issuing hydrologic forecast products with the NWS Advanced Hydrologic Prediction System (AHPS).  AHPS is described by Deweese (2002).

X.  References

Deweese, M.M.. (2002) AHPS Procedures and Products at the NCRFC < http://www.crh.noaa.gov/ncrfc/WebShows/AHPSRfc/sld001.htm >.
Dunne, T., Leopold, L.B. (1978) Water in Environmental Planning; pp. 477‑499.
Kling, G.W. et. al. (April, 2003) “Confronting Climate Change In the Great Lakes Region < http://www.ucsusa.org/greatlakes/glchallengetechbac.html >.
Neuman, P.J.(1999) Hydrologic Forecast Procedures & Spring Flood Outlooks, Upper Midwest < http://www.crh.noaa.gov/ncrfc/documents/Papers/Outlooks/Outlooks.htm >.
Neuman P. J. (April, 2003) Special Report – Air Temperatures & Dew Points, Great Lakes States <  http://www.mnforsustain.org/mn_dewpoints_neuman_p_special_report.htm >.
Used with permission of the author.

Snowmelt & Dewpoints: Table 1 & Figure 1
Snowmelt & Dewpoints: Table 2 -Minneapolis- Data
Snowmelt & Dewpoints: Figure 2 -Fargo- +Data
Snowmelt & Dewpoints: Figure 3 -Duluth- +Data
Snowmelt & Dewpoints: Figure 4, Eau Claire, +Data

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