Konstantin Y. Vinnikov
and Alan Robock
Department of Meteorology, University of Maryland, College Park
Nina A. Speranskaya
State Hydrological Institute, St. Petersburg, Russia
Russian Hydrometeorological Center, Moscow
For different scientists, soil moisture is a component of the water budget of the upper soil layer (hydrology), of water resources available for agricultural crops and natural vegetation (agrometeorology), or of meteorological memory (weather and climate predictions). Unfavorable change in the soil moisture regime may be an important problem in the future due to greenhouse global warming. In the United States and Western Europe, there were never any national observing programs of this important earth system element, but we are fortunate that gravimetric observation of soil moisture was started in the 1930's in the Former Soviet Union (FSU) at few hundred and later at more than 3000 meteorological stations and the data were published in reference books. Multi-year averages for administrative districts and some time series were published by Meshcherskaya et al. (1982), Kelchevskaya (1989), and Zhukov (1986). Kelchevskaya (1983), Vinnikov and Yeserkepova (1991), Robock et al. (1995), and Vinnikov et al. (1996) used Russian gravimetric soil moisture data for various analyses.
The complex topography of natural landscapes, with spatially variable vegetation and soil types, and gravitational drainage and infiltration of water after heavy rains, are responsible for small-scale spatial (tens of meters) and temporal (up to few days) variability in the soil moisture field. This component of soil moisture field variability looks like random (white) noise in comparison with the long-term (about 1-4 months) and large-scale (about 400-800 km) signal related to atmospheric forcing (Meshcherskaya et al., 1982; Delworth and Manabe, 1988, 1989; Vinnikov and Yeserkepova, 1991; Vinnikov et al., 1996). One of the traditional empirical methods to eliminate white noise in soil moisture fields consists of spatial averaging of all measurements of stations inside separate administrative districts (Meshcherskaya et al., 1982; Kelchevskaya, 1983; Zhukov, 1986). This approach is used here to examine the large-scale and long-term component in variations of soil moisture of the territory of the Former Soviet Union.
Six different sets of soil moisture data are currently available to the scientific community and may now be retrieved electronically from the Global Soil Moisture Data Bank.
Three of the data sets are available as ASCII text and as GrADS binary data. We also provide FORTRAN programs to read the data and create GrADS files, and GrADS execs to display maps of the data. The GrADS station data function OACRES (Objective Analysis using the CRESsman (1959) scheme) with default parameters was used to interpolate the initial data into a 1°x1° grid. The GrADS exec files display maps of plant-available soil water content in the upper 10, 20, or 50 cm, and upper 100 cm of soil, and also maps of the ratio of water content in the two soil layers. The data sets are: RUSWET-GRASS-130STA (Plant-available soil moisture data and maps, 1978-1985; Former Soviet Union; Data for natural vegetation (grass)), RUSWET-AGROCLIM (Climatic data and maps; Multi-year average of plant-available soil moisture; Former Soviet Union; Data for agricultural fields with winter and spring cereal crops), and RUSWET-AGRO (Plant-available soil moisture data and maps, 1987-1988; Former Soviet Union; Data for agricultural fields with winter and spring cereal crops):
RUSWET-GRASS-130STA. This data set contains soil moisture gravimetric measurements made during 1978-1985 at 130 meteorological stations of the FSU. It contains plant-available soil moisture for the upper 10 cm and 1 m soil layers at flat observational plots with natural grass vegetation. The size of the observational plots is about 0.1 ha. Observations are made with temporal resolution of 10 days during the warm season (3 times per month - on the 8th, 18th and 28th days of each month), and once a month (on the 28th day of the month) during the winter. The time series contain 36 values per year, with a code for missing data if data are absent. The data for 1978-1985 are a small part of the data which are published in annual reference books. More information about 50 of these stations can be found in Vinnikov and Yeserkepova (1991). Robock et al. (1995) and Yang et al. (1997) used data for 6 of these stations in their demonstration of soil moisture simulations with 2 different land surface models forced with atmospheric observations, and the forcing data for these 6 stations are also available at the same WWW address. Figure 1a shows an example of the data for the end of May 1985.
RUSWET-AGROCLIM. The data used here are multi-year averages of plant-available water content in the soil layers 0-20 cm, 0-50 cm and 0-100 cm at agricultural fields with winter cereal crops and spring cereal crops (given separately) for 144 administrative districts of the FSU. Winter cereals are the best analog for natural grasslands. Spring cereals are representative of many agricultural regions of the FSU. The number of stations used for spatial averaging for each district varied from about 10 to more than 100. The period of observation is 1946-1980 for the western part of the FSU and 1927-1982 for the eastern part. All the data were retrieved and digitized from two Russian reference books (Zhukov, 1986; Kelchevskaya, 1989). As an example, Figure 1b displays climatic maps of soil moisture content at agricultural fields with spring cereals for the end of May.
RUSWET-AGRO. This data set is the output of a system for monitoring soil moisture at agricultural fields of the former Soviet Union. The data set contains plant-available soil moisture for the upper 20 cm and 1 m soil layers at agricultural fields with winter cereal crops and spring cereal crops (given separately) for 102 administrative districts of the former Soviet Union. The measurements of about six stations (on average) were used for each district with equal weights. Gravimetric soil moisture observations from about 600 agrometeorological stations were used as the basis for the data set. The spatial domain of the data is the grain belt of the FSU (Russia, Ukraine, Belarus, Moldova, Lithuania, Latvia, Estonia, and Kazakhstan). On average, the area of each district is about 30,000 km2 (ranging from 10,000 to more than 100,000 km2). The temporal domain is 1987-1988; the growing period is from April 8 to October 28, for each year, and the temporal resolution is 10 days (3 measurements per month). The data set for 1987-1988 was created for use in the GEWEX/ISLSCP Global Soil Wetness Project for validation of model-estimated soil moisture variations. We are now working to make all the data for 1958-1996 available to the scientific community, and they will soon be available at the same WWW site. As an example, Figure 1c displays maps of soil moisture content at agricultural fields with spring cereals for the end of May 1987.
There are three other Russian data sets available:
RUSWET-GRASS-50STA. This is the 50 station data set of Russian (former Soviet Union) plant-available soil moisture measurements at natural grass fields. The data set consists of measurements of plant available soil moisture in the top 1 meter of soil at 10-day intervals (on the 8th, 18th, and the end of each month). The measurements were made on a level grass field (natural vegetation) at each station site using a gravimetric technique. A detailed description of these data is given by Vinnikov and Yeserkepova (1991). Some of these stations are also represented in the RUSWET-GRASS-130STA data set.
Robock et al.
(1995) and Yang
et al. (1997) used 6 stations from the Vinnikov and Yeserkepova
archive (also in the 130-station
archive) to demonstrate that land surface models, when forced with
actual meteorological and actinometric data, can be evaluated by comparison
with actual soil moisture, snow depth, albedo, and net radiation observations.
moisture data are available here. The forcing
and other validation data and a subset
of depth of frozen soil layers data are also available. These data
have been used by a number of land surface groups to exercise their models,
and we encourage further use of these data by others.
RUSWET-VALDAI. The Project for Intercomparison of Landsurface Parameterization Schemes (PILPS) (Henderson-Sellers et al., 1993) evaluates soil moisture models in several ways. Data from a grassland catchment at the Valdai Russia research station are being used for the PILPS 2d experiment to test many different land surface models in a climate with seasonal snow cover for an 18-year period. Forcing data for Valdai and a Read Me File are now available. Schlosser et al. (1997) have already conducted this experiment for bucket and SSiB models. When the PILPS 2d runs are complete, we will distribute the validation data as described by Vinnikov et al. (1996).
Currently, we are also preparing new soil moisture data sets for India,
China, and Mongolia.
Acknowledgments. This work was supported by NOAA grants NA36GPO311
and NA56GPO212 and NASA grants NCC555 and NAGW5227.
Cressman G. P., 1959: An operational objective analysis system. Monthly
Weather Review, 87, 367-374.
Delworth, T. L., and S. Manabe, 1988: The influence of potential evaporation
on the variabilities of simulated soil wetness and climate. J. Climate,
Delworth, T. L., and S. Manabe, 1989: The influence of soil wetness
on near-surface atmospheric variability. J. Climate, 2, 1447-1462.
Henderson-Sellers, Z.-L. Yang and R.E. Dickinson, 1993, The Project for Intercomparison of Land-surface Parameterization Schemes, Bull. of the Amer. Met. Soc., 74, 1335-1349.
Kelchevskaya, L. S., 1983: Soil moisture of the European part of USSR.
(Gidrometeoizdat, Leningrad), 183 pp. (In Russian).
Kelchevskaya, L. S., Ed., 1989: Mean long term stores of productive
water under winter and early spring cereals in districts, regions, republics
and economic regions. Reference book. Vol. 2. Ural, Western and Eastern
Siberia, Kazakhstan, Central Asia. (Gidrometeoizdat, Leningrad), 65 pp.
Meshcherskaya, A. V., N. A. Boldyreva, and N. D. Shapaeva, 1982: District
average plant available soil water storage and the depth of snow cover.
Statistical analysis and its usage (some examples). (Gidrometeoizdat, Leningrad),
243 pp. (In Russian).
Robock, A., K. Y. Vinnikov, C. A. Schlosser, N. A. Speranskaya, and
Y. Xue, 1995: Use of midlatitude soil moisture and meteorological observations
to validate soil moisture simulations with biosphere and bucket models.
J. Climate, 8, 15-35.
Schlosser, C. Adam, Alan Robock, Konstantin Ya. Vinnikov, Nina A. Speranskaya,
and Yongkang Xue, 1997: 18-year land-surface hydrology model simulations
for a midlatitude grassland catchment in Valdai, Russia. Mon. Weather
Rev., in press.
Vinnikov, K. Y. and I. B. Yeserkepova, 1991: Soil moisture: empirical
data and model results. J. Climate, 4, 66-79.
Vinnikov, K. Y., A. Robock, N. A. Speranskaya, and C. A. Schlosser, 1996: Scales of temporal and spatial variability of midlatitude soil moisture. J. Geophys. Res., 101, 7163-7174. ABSTRACT
Yang, Z.-L., R. E. Dickinson, A. Robock, and K. Y. Vinnikov, 1997: On validation of the snow sub-model of the Biosphere-Atmosphere Transfer Scheme with Russian snow cover and meteorological observational data. J. Climate, 10, 353-373. ABSTRACT
Zhukov, V. A., Ed., 1986: Mean long term stores of productive water
under winter and early spring cereals in districts, regions, republics
and economic regions. Reference book. Vol. 1. European part of the USSR.
(Gidrometeoizdat, Leningrad), 122 pp. (in Russian)