United States Great Plains Research Articles

Estimating root zone soil moisture using near-surface observations from SMOS

Abstract. Satellite-derived soil moisture provides more spatially and temporally extensive data than in situ observations. However, satellites can only measure water in the top few centimeters of the soil. Root zone soil moisture is more important, particularly in vegetated regions. Therefore estimates of root zone soil moisture must be inferred from near-surface soil moisture retrievals. The accuracy of this inference is contingent on the relationship between soil moisture in the near-surface and the soil moisture at greater depths. This study uses cross correlation analysis to quantify the association between near-surface and root zone soil moisture using in situ data from the United States Great Plains. Our analysis demonstrates that there is generally a strong relationship between near-surface (5–10 cm) and root zone (25–60 cm) soil moisture. An exponential decay filter is used to estimate root zone soil moisture using near-surface soil moisture derived from the Soil Moisture and Ocean Salinity (SMOS) satellite. Root zone soil moisture derived from SMOS surface retrievals is compared to in situ soil moisture observations in the United States Great Plains. The SMOS-based root zone soil moisture had a mean R2 of 0.57 and a mean Nash–Sutcliffe score of 0.61 based on 33 stations in Oklahoma. In Nebraska, the SMOS-based root zone soil moisture had a mean R2 of 0.24 and a mean Nash–Sutcliffe score of 0.22 based on 22 stations. Although the performance of the exponential filter method varies over space and time, we conclude that it is a useful approach for estimating root zone soil moisture from SMOS surface retrievals.

Spatial patterns of land surface phenology relative to monthly climate variations: US Great Plains

We extracted and mapped six land surface phenological metrics including: (1) the peak normalized difference vegetation index (NDVI), (2) peak date, (3) start of season (SOS), (4) end of season (EOS), (5) length of growing season (LOS), and (6) cumulative NDVI from 2000 to 2009 using Moderate-Resolution Imaging Spectroradiometer (MODIS) images covering the United States (US) Great Plains. Their patterns relative to monthly precipitation, maximum temperature, minimum temperature, and dew points were analyzed using multiple linear regression, stepwise selection, and geographically weighted regression (GWR) analysis. Both peak NDVI and cumulative NDVI had similar spatial patterns. Their values decreased along an east to west gradient. Peak date and SOS also showed compatible patterns. The southeastern Great Plains had the earliest SOS, peak date, and the longest LOS, given its warmer temperatures and greater precipitation. Dew points in March and October as well as the maximum temperature in April highly influenced the SOS, while dew point in August was found more influential for EOS and LOS. Precipitation in March and September also affected the total cumulative NDVI. The GWR models performed better than the OLS because the GWR utilized the spatial relationships between the different variables resulting from local level processes. The regression models predicted peak NDVI and cumulative NDVI better than the other phenological indices.

Past and future extreme climatic events in Canadian prairies: Integrating economics and climate

T occurrence of dry & wet events causes major adverse impacts in the Canadian Prairies. In the past, dry events, which are typically agricultural and/or hydrological droughts, have been common in the region. At least five major drought episodes have occurredin the Canadian Prairies during the past 120 years. These include multi-year droughts in the 1890s, 1910s, 1930s, late 1950s to early 1960s, 1980s, 1999-2005, 2009-10. The years 2001-2004 resulted in one of the largest area multi-year drought. Almost half of the agricultural prairies were in severe drought or worse during 2001. For the older droughts of the 1900 to 1950 period, the 1930s were the largest multi-year droughts, and 1961 and 1919 were the single-year severe droughts that covered the largest area. According to Bonsal et al. (2011), some of the major droughts have migrated into the Canadian Prairies from the United States Great Plains, including the 1999-2005 drought. This means that it is important to monitor the northern US droughts for expansion or migration into Canada.In the future, the frequency of both droughts and intense precipitation areexpected to increase. In fact, the review by Wheaton et al. (2013) found that (i) multi-year droughts (e.g., 5 to 10 years, or so) would occur more than twice as often forthe period to 2100; (ii) they would come with more evaporative power and be more intense as they will have much higher temperatures and much longer warm seasons; and (iii) they would cover much more area than even the across-Canada drought of 2001-2002. Droughts of such magnitudes would have devastating impacts on the Prairies, economically, environmentally, and socially, particularly on those industries where weather is a major determining factor to their survival and performance. One such industry is agriculture. It is the contention of this paper that estimation of impacts of the past droughts has been limited in scope, and may have underestimated these impacts. This under-estimation may be a result of several reasons: (i) Past studies have typically measured these impacts for only the drought period. In reality a drought would affect some of the enterprises (such as livestock production) that take several years to completely result in an economic gain to the producers. (ii) Although private costs of the people impacted by droughts are measured, the macro-level changes causing hardships to people and businesses are not measured. (iii) Droughts may impact ecological goods and services which can then affect the society at large. (iv) Loss to human capital through stress, sickness, and loss of employment as well as other changes that lead to lost productivity are typically not included. (v) Fiscal costs to the governments and their resulting impact on other programs have not been estimated. (vi) Economic hardships to smaller communities and people living therein have also not been addressed. We recommend that future investigations attempt to redress these deficiencies in the method of estimation of social, environmental and economic impacts of droughts. Impacts of the recent severe droughts in the US Plains and Canadian Prairies are reminders that current adaptation can be improved.

The effect of rate of change, variability, and extreme events on the pace of adaptation to a changing climate

When is it time to adopt different technologies, management strategies, and resource use practices as underlying climate change occurs? We apply risk and decision analysis to test hypotheses about the timing and pace of adaption in response to different profiles of climate change and extremes expressed as yield and income variation for a simulated dryland wheat farm in the United States Great Plains. Climate scenarios include gradual change with typical or increased noise (standard deviation), rapid and large change, and gradual change with extreme events stepped through the simulation. We test decision strategies that might logically be utilized by farmers facing a climate trend that worsens crop enterprise outcomes. Adaptation quickens with the rate of change, especially for decision strategies based on performance thresholds, but is delayed by larger climate variability, especially for decision strategies based on recognizing growing differential between adaptive and non-adaptive performance. Extreme events evoke adaptation sooner than gradual change alone, and in some scenarios extremes evoke premature, inefficient, adaptation.

Quantifying climate change mitigation potential in the United States Great Plains wetlands for three greenhouse gas emission scenarios

We examined opportunities for avoided loss of wetland carbon stocks in the Great Plains of the United States in the context of future agricultural expansion through analysis of land-use land-cover (LULC) change scenarios, baseline carbon datasets and biogeochemical model outputs. A wetland map that classifies wetlands according to carbon pools was created to describe future patterns of carbon loss and potential carbon savings. Wetland avoided loss scenarios, superimposed upon LULC change scenarios, quantified carbon stocks preserved under criteria of carbon densities or land value plus cropland suitability. Up to 3420 km2 of wetlands may be lost in the region by 2050, mainly due to conversion of herbaceous wetlands in the Temperate Prairies where soil organic carbon (SOC) is highest. SOC loss would be approximately 0.20 ± 0.15 megagrams of carbon per hectare per year (MgC ha−1 yr−1), depending upon tillage practices on converted wetlands, and total ecosystem carbon loss in woody wetlands would be approximately 0.81 ± 0.41 MgC ha−1 yr−1, based on biogeochemical model results. Among wetlands vulnerable to conversion, wetlands in the Northern Glaciated Plains and Lake Agassiz Plains ecoregions exhibit very high mean SOC and on average, relatively low land values, potentially creating economically competitive opportunities for avoided carbon loss. This mitigation scenarios approach may be adapted by managers using their own preferred criteria to select sites that best meet their objectives. Results can help prioritize field-based assessments, where site-level investigations of carbon stocks, land value, and consideration of local priorities for climate change mitigation programs are needed.

Predicting the elements

On 20 May this year, a massive and powerful tornado hit Moore, Oklahoma. With peak winds of 340km/h, the 2km wide tornado tore through the heavily populated town on a 27km long path across the Oklahoma City region, killing 24 people and ripping down 13,000 homes, schools, farms and businesses. Water supplies were cut, more than 61,500 power outages were registered and Oklahoma Department for Insurance estimates claims will top $1bn. This twister was one of 53 in a large, violent weather system that swept across the midwestern United States and lower Great Plains from 18 to 21 May, killing two more people. What's more, this spate of tornadoes came only a day after a 23-strong outbreak that spanned Texas, Louisiana and Alabama, killing six people. Set these against a back-drop of hurricanes, earthquakes, floods, and tsunamis that take place worldwide, year in, year out, and one fact becomes very clear; each and every extreme weather event is so very difficult to predict.

Draw-a-Person-in-the-Rain: Does Geographic Location Matter?

This pilot study examines an aspect of construct validity of the Draw-a-Person-in-the-Rain (DAPR) assessment utilizing a sample (N = 58) of third-grade public school children from three geographic regions of the United States (Great Plains, Rocky Mountain, and Pacific Northwest) that differ in climate and frequency of precipitation. A scoring system was used to indicate the presence or absence of environmental elements depicted in the drawings. Results indicate a significant difference between the scores on drawings from the Great Plains and those from the Pacific Northwest sites, suggesting that the typical precipitation pattern of a given region may influence how a person responds to the DAPR task. Although findings are preliminary, they suggest that further examination of the validity of the DAPR is needed.

Variation in total electron content above large thunderstorms

AbstractTotal electron content (TEC) measured by Global Positioning System (GPS) receivers in the United States Great Plains is examined for three nights with large thunderstorms and for one night with little thunderstorm activity. The GPS TEC data are fit with a polynomial, and the variations are estimated by subtracting this fit from the data. We found that anomalous TEC variations are closely associated in time and space to the large underlying thunderstorms. The largest storm‐related TEC variation is observed to be ~1.4 total electron content unit (TECU) over a typical nighttime background value of several TECUs. The variations near the storm appear to have more high‐frequency content than those away from the storm, with periods of minutes to tens of minutes. No detectable localized TEC variation is observed for the thunderstorm‐quiet night.

Steps towards a mechanistic model of global soil nitric oxide emissions: implementation and space based-constraints

Abstract. Soils have been identified as a major source (~15%) of global nitrogen oxide (NOx) emissions. Parameterizations of soil NOx emissions (SNOx) commonly used in the current generation of chemical transport models were designed to capture mean seasonal behaviour. These parameterizations do not, however, respond quantitatively to the meteorological triggers that are observed to result in pulsed SNOx. Here we present a new parameterization of SNOx implemented within a global chemical transport model (GEOS-Chem). The parameterization represents available nitrogen (N) in soils using biome specific emission factors, online wet- and dry-deposition of N, and fertilizer and manure N derived from a spatially explicit dataset, distributed using seasonality derived from data obtained by the Moderate Resolution Imaging Spectrometer. Moreover, it represents the functional form of emissions derived from point measurements and ecosystem scale experiments including pulsing following soil wetting by rain or irrigation, and emissions that are a smooth function of soil moisture as well as temperature between 0 and 30 °C. This parameterization yields global above-soil SNOx of 10.7 Tg N yr−1, including 1.8 Tg N yr−1 from fertilizer N input (1.5% of applied N) and 0.5 Tg N yr−1 from atmospheric N deposition. Over the United States (US) Great Plains region, SNOx are predicted to comprise 15–40% of the tropospheric NO2 column and increase column variability by a factor of 2–4 during the summer months due to chemical fertilizer application and warm temperatures. SNOx enhancements of 50–80% of the simulated NO2 column are predicted over the African Sahel during the monsoon onset (April–June). In this region the day-to-day variability of column NO2 is increased by a factor of 5 due to pulsed-N emissions. We evaluate the model by comparison with observations of NO2 column density from the Ozone Monitoring Instrument (OMI). We find that the model is able to reproduce the observed interannual variability of NO2 (induced by pulsed-N emissions) over the US Great Plains. We also show that the OMI mean (median) NO2 observed during the overpass following first rainfall over the Sahel is 49% (23%) higher than in the five days preceding. The measured NO2 on the day after rainfall is still 23% (5%) higher, providing a direct measure of the pulse's decay time of 1–2 days. This is consistent with the pulsing representation used in our parameterization and much shorter than 5–14 day pulse decay length used in current models.

Performance of a Wind-Profiling Lidar in the Region of Wind Turbine Rotor Disks

Abstract As the wind energy sector continues to grow, so does the need for reliable vertical wind profiles in the assessment of wind resources and turbine performance. In situ instrumentation mounted on meteorological towers can rarely probe the atmosphere across the full span of modern turbine rotor disks, which typically extend from 40 to 120 m above the surface. However, by measuring the Doppler shift of laser light backscattered by particles in the atmosphere, remote sensing lidar is capable of estimating wind speeds and turbulence at several altitudes in this range and above. Consequently, lidar has proven a promising technology for both wind resource assessment and turbine response characterization. The aim of this study is to quantify data availability for a coherent detection wind-profiling lidar—namely, the Leosphere Windcube. To determine situations of suitable data return rates, a Windcube, collocated with a Vaisala CL31 ceilometer, was deployed as part of the Skywatch Observatory at the University of Colorado at Boulder. Aerosol backscatter, as measured by the ceilometer, and lidar carrier-to-noise ratio (CNR) are strongly correlated. Additionally, lidar CNR was found to depend on atmospheric turbulence characteristics and relative humidity in another deployment at a location in the United States Great Plains. These relationships suggest an ability to predict lidar performance based on widely available air quality assessments (such as PM2.5 concentration) and other climatic conditions, thus providing guidance for determining the utility of lidar deployments at wind farms to characterize turbine performance.

Influence of land-use and conservation programs on wetland plant communities of the semiarid United States Great Plains

Depressional wetlands are predominant surface hydrological features providing critical societal ecosystem services in the semiarid United States High Plains. Critical wetland properties may be threatened because this 30 million ha short-grass prairie largely was converted from grassland to cropland. Further, the United States Department of Agriculture enrolled marginal cropland into the Conservation Reserve Program (CRP). CRP reduces topsoil erosion by planting permanent cover on croplands. In the High Plains, introduced tall-grasses primarily were planted in CRP, possibly reducing precipitation runoff, an important hydroperiod driver in wetlands. We assessed land-use influence on important wetland processes (wetland area, inundation, and plant composition) in 261 depressional wetlands called playas (87 each in native grassland, CRP, and cropland). Surveys spanned six states within three High Plains sub-regions (southern, central and northern). Playas averaged 8ha in cropland and 16ha in other land-uses. Plant composition in grassland playas was predominately native perennials, and upland plant cover equaled wetland plant cover. Cropland playas had fewer species/ha, generally more annuals than perennials and 80% greater exposed ground than other land-uses. CRP playas had 400% greater cover of introduced species (mostly upland perennial tall-grasses), which possibly inhibited catchment runoff, as CRP playas were inundated 56% less often than other land-uses. Therefore, tall grasses should not be planted in short-grass prairie CRP catchments, as they alter inundation frequency and vegetation communities in embedded wetlands. Conservation programs containing provisions to protect playas, including planting common native species and using grass buffers to control erosion into wetlands, should be promoted.

Land change variability and human–environment dynamics in the United States Great Plains

Land use and land cover changes have complex linkages to climate variability and change, biophysical resources, and socioeconomic driving forces. To assess these land change dynamics and their causes in the Great Plains, we compare and contrast contemporary changes across 16 ecoregions using Landsat satellite data and statistical analysis. Large-area change analysis of agricultural regions is often hampered by change detection error and the tendency for land conversions to occur at the local-scale. To facilitate a regional-scale analysis, a statistical sampling design of randomly selected 10 km × 10 km blocks is used to efficiently identify the types and rates of land conversions for four time intervals between 1973 and 2000, stratified by relatively homogenous ecoregions. Nearly 8% of the overall Great Plains region underwent land-use and land-cover change during the study period, with a substantial amount of ecoregion variability that ranged from less than 2% to greater than 13%. Agricultural land cover declined by more than 2% overall, with variability contingent on the differential characteristics of regional human–environment systems. A large part of the Great Plains is in relatively stable land cover. However, other land systems with significant biophysical and climate limitations for agriculture have high rates of land change when pushed by economic, policy, technology, or climate forcing factors. The results indicate the regionally based potential for land cover to persist or fluctuate as land uses are adapted to spatially and temporally variable forcing factors.

Connectivity in piping plovers: Do breeding populations have distinct winter distributions?

AbstractResightings of uniquely marked birds from 2001 to 2008 were used to determine winter distributions of 4 breeding populations of a species at risk, the piping plover (Charadrius melodus). Although considerable overlap exists, a distinct pattern in winter distributions was evident. Birds originating from eastern Canada wintered farthest north compared to other populations. Most individuals from the United States Great Lakes were found in South Carolina and Georgia in winter, whereas birds from eastern Canada were found primarily in North Carolina. Although the great majority of birds marked in Prairie Canada were observed wintering in Texas, particularly southern Texas, breeding plovers from the United States Great Plains were more widely distributed on the gulf coast from Florida to Texas. Very few large‐scale movements of individuals in winter were reported either within or between years. This study highlights the significance of geographic regions for eastern Canada, the United States Great Lakes, the United States Great Plains, and Prairie Canada populations, and demonstrates relatively high winter site fidelity. This information will help focus conservation efforts for specific breeding populations during the winter. © 2011 The Wildlife Society.

Household and farm transitions in environmental context

Recent debate in the literature on population, environment, and land use questions the applicability of theory that patterns of farm extensification and intensification correspond to the life course of farmers and to the life cycle of farm families. This paper extends the debate to the agricultural development of the United States Great Plains region, using unique data from 1875 to 1930 that link families to farms over time in 25 environmentally diverse Kansas townships. Results of multilevel statistical modeling indicate that farmer's age, household size, and household structure are simultaneously related to both the extent of farm operations and the intensity of land use, taking into account local environmental conditions and time trends as Kansas was settled and developed. These findings validate farm- and life cycle theories and offer support for intergenerational motivations for farm development that include both daughters and sons. Environmental variation in aridity was a key driver of farm structure.

The WRF Model Forecast-Derived Low-Level Wind Shear Climatology over the United States Great Plains

For wind resource assessment projects, it is common practice to use a power-law relationship (U(z) ~ zα) and a fixed shear exponent (α = 1=7) to extrapolate the observed wind speed from a low measurement level to high turbine hub-heights. However, recent studies using tall-tower observations have found that the annual average shear exponents at several locations over the United States Great Plains (USGP) are significantly higher than 1=7. These findings highlight the critical need for detailed spatio-temporal characterizations of wind shear climatology over the USGP, where numerous large wind farms will be constructed in the foreseeable future. In this paper, a new generation numerical weather prediction model—the Weather Research and Forecasting (WRF) model, a fast and relatively inexpensive alternative to time-consuming and costly tall-tower projects, is utilized to determine whether it can reliably estimate the shear exponent and the magnitude of the directional shear at any arbitrary location over the USGP. Our results indicate that the WRF model qualitatively captures several low-level wind shear characteristics. However, there is definitely room for physics parameterization improvements for the WRF model to reliably represent the lower part of the atmospheric boundary layer.

Barchan dunes stabilized under recent climate warming on the northern Great Plains

We use light detection and ranging (LIDAR) imagery and optical stimulation luminescence dating to show that stable parabolic dunes on the Canadian prairies originated from active barchan dunes ~200 years ago. Residual dune ridges, marking former lower stoss slope positions of migrating dunes, record the transformation of barchan dunes to parabolic dunes between A.D. 1810 and 1880. Parabolic dunes stabilized by ca. A.D. 1910, with a few larger dunes and blowouts still active today. A dry, cool climate permitted sand transport to out-compete vegetation stabilization and, with lowered water tables, maintain desert-like barchan dunes with bare interdune sand sheets. These findings explain why dune fields of the southern Canadian prairies are currently more active than those of the United States Great Plains and the observation that dunes have stabilized under twentieth century warming. Our results emphasize the importance of viewing dune field responses to short-term disturbances in the context of longer-term system response, particularly when relatively modest climatic changes can cause major shifts in dune activity.

Role of convection triggers in the simulation of the diurnal cycle of precipitation over the United States Great Plains in a general circulation model

Recent comparisons of a number of general circulation models (GCMs) have shown that most of them have deficiencies in the simulation of the diurnal cycle of warm season precipitation. The deficiencies are particularly pronounced over the United States Great Plains where the models generally fail to capture the nocturnal rainfall maximum found in the observations. By using the National Centers for Environmental Prediction's Global Forecasting System (NCEP GFS) GCM, which is unusual in that it produces a realistic nocturnal rainfall signal over the Great Plains, this study examines the nature and realism of the mechanisms responsible for the nocturnal rain in the GCM. A series of sensitivity experiments highlight the importance of triggers implemented in the convection scheme. Specifically, the convection trigger function that the cloud base (defined as the level of free convection) must be within 150 hPa depth from the convection starting level (which crudely represents an upper limit of convective inhibition) plays a key role on the realistic simulation of the diurnal phase of convection. On the basis of this trigger, the nighttime elevation of the convection starting level (defined as the maximum level of moist static energy from the surface) above the boundary layer inversion provides the condition favorable for the development of nocturnal precipitation over the Great Plains. The results are discussed in terms of their implications for improving our understanding and parameterizations of the physical processes that generate nocturnal rain in this and other regions with large diurnal cycles.

A land-surface process/radiobrightness model with coupled heat and moisture transport for freezing soils

Phase change of water is an important sink and source of energy and moisture within soils as well as a significant influence upon soil temperature and moisture profiles. These profiles play a crucial role in governing energy and moisture fluxes between bare soils and the atmosphere. They also codetermine radiobrightness, so that the difference between modeled and observed radiobrightness becomes a measure of error in a model's estimate of temperature or moisture. The authors present a physically based, coupled-heat and moisture-transport, one-dimensional hydrology/radiobrightness (1 dH/R) model for bare, freezing and thawing, moist soils that are subject to insolation, radiant heating and cooling, and sensible and latent heat exchanges with the atmosphere. They use this model to examine thermal, hydrologic, and Special Sensor Microwave/Imager (SSMI) radiobrightness signatures for a three-month, dry-down simulation in the fall and winter of the northern United States Great Plains as part of an investigation of the effects of coupling heat and moisture transport. Given a typical initial moisture content of 38%, they find that coupled transport results in a reduction of ice in the surface soil by 21%. The range of diurnal variations in temperature are not significantly affected by coupled transport. Diurnal variations in the 19-GHz, H-polarized radiobrightness can be greater in the coupled transport case by 37 K. Total diurnal variation can exceed 57 K during periods of diurnal freezing and thawing.

The Climate Signal in Regional Moisture Fluxes: A Comparison of Three Global Data Assimilation Products

This study assesses the quality of estimates of climate variability in moisture flux and convergence from threeassimilated datasets: two are reanalysis products generated at the Goddard Data Assimilation Office and theNational Centers for Environmental Prediction–National Center for Atmospheric Research, and the third consistsof the operational analyses generated at the European Centre for Medium-Range Weather Forecasts (ECMWF).The regions under study (the United States Great Plains, the Indian monsoon region, and Argentina east of theAndes) are characterized by frequent low-level jets and other interannual low-level wind variations tied to thelarge-scale flow. While the emphasis is on the reanalysis products, the comparison with the operational productis provided to help assess the improvements gained from a fixed analysis system. All three analyses capture the main moisture flux anomalies associated with selected extreme climate (droughtand flood) events during the period 1985–93. The correspondence is strongest over the Great Plains and weakestover the Indian monsoon region reflecting differences in the observational coverage. For the reanalysis products,the uncertainties in the lower tropospheric winds is by far the dominant source of the discrepancies in themoisture flux anomalies in the middle latitude regions. Only in the Indian Monsoon region, where interannualvariability in the low-level winds is comparatively small, does the moisture bias play a substantial role. Incontrast, the comparisons with the operational product show differences in moisture that are comparable to thedifferences in the wind in all three regions. Compared with the fluxes, the anomalous moisture convergences show substantially larger differences amongthe three products. The best agreement occurs over the Great Plains region where all three products showvertically integrated moisture convergence during the floods and divergence during the drought with differencesin magnitude of about 25%. The reanalysis products, in particular, show good agreement in depicting the differentroles of the mean flow and transients during the flood and drought periods. Differences between the threeproducts in the other two regions exceed 100% reflecting differences in the low-level jets and the large-scalecirculation patterns. The operational product tends to have locally larger amplitude convergence fields, whichaverage out in area-mean budgets: this appears to be at least in part due to errors in the surface pressure fieldsand aliasing from the higher resolution of the original ECMWF fields. On average, the reanalysis products show higher coherence with each other than with the operational productin the estimates of interannual variability. This result is less clear in the Indian monsoon region where differencesin the input observations appear to be an important factor. The agreement in the anomalous convergence patternsis, however, still rather poor even over relatively data-dense regions such as the United States Great Plains.These differences are attributed to deficiencies in the assimilating general circulation model’s representations ofthe planetary boundary layer and orography, and a global observing system incapable of resolving the highlyconfined low-level winds associated with the climate anomalies.

Merging operational satellite and historical station snow cover data to monitor climate change

Since the middle of 1987, snow cover Northern Hemisphere lands has been less extensive than at any time since the advent of reliable satellite snow charting in 1972. In fact, 1990 should of down as being the lowest snow year on record: monthly minima have been established for February through September (based on observations through September). However, with less than a two-decade long record of satellite observations of snow cover, it is impossible to place this recent dearth of cover in proper perspective. To do so requires a longer period of record, one which can only be supplied from station data. Regional intercomparisons of visible satellite-derived snow products and networks of station observations agree well on a seasonal time scale, given a network of high-quality stations in non-mountainous terrain. Thus, where these conditions are met, lengthy time series of regional snow cover may be compiled confidently from station observations, permitting documentation of natural fluctuations and trends of cover that may occurred over the past century. For instance, decadal fluctuations in snow cover have been identified over the United States Great Plains this century, and a trend towards increasing duration of cover from the 1930's to 1970's has been observed in the central Plains. Such information enhances the utility of satellite-derived snow cover observations identifying and monitoring future climate change.