Positive Soil Moisture Research Articles

Observational relationship of sea surface temperatures and precedent soil moisture with summer precipitation in the U.S. Great Plains

AbstractIn this study, the relationship between precedent soil moisture anomalies and summer precipitation in the U.S. Great Plains was examined using Variable Infiltration Capacity (VIC)‐simulated soil moisture and the Standardized Precipitation Index (SPI). The influence of Niño sea surface temperatures (SSTs) on summer precipitation was also investigated to compare their relative contributions to those from local moisture recycling.Results indicate that spring (May 1st) soil moisture is significantly correlated with summer SPI only during periods when Niño SSTs are not strongly correlated with summer SPI (e.g. 1920s–1930s). During periods when Niño SSTs are strongly correlated with summer SPI (e.g. 1940s–1980s), spring soil moisture is not a good predictor of summer precipitation in the U.S. Great Plains. The periods of strong correlation between Niño SSTs and summer precipitation are associated with strong SST persistence. Results also indicate that the impact of soil moisture anomalies and SST on summer precipitation varies greatly in space and time. Positive soil moisture–precipitation correlations are generally associated with high soil moisture persistence and negative soil moisture–precipitation correlations are linked to low soil moisture persistence. In addition, high SST persistence tends to favour (inhibit) negative (positive) soil moisture–precipitation correlations. This study suggests that both local soil moisture and remote SST anomalies influence summer precipitation in the U.S. Great Plains. The soil moisture anomalies are of greatest importance during years when Niño SST persistence is low. Copyright © 2009 Royal Meteorological Society

Evaluating the Influence of Antecedent Soil Moisture on Variability of the North American Monsoon Precipitation in the Coupled MM5/VIC Modeling System

The influence of antecedent soil moisture on North American monsoon system (NAMS) precipitation variability was explored using the MM5 mesoscale model coupled with the Variable Infiltration Capacity (VIC) land surface model. Sensitivity experiments were performed with extreme wet and dry initial soil moisture conditions for both the 1984 wet monsoon year and the 1989 dry year. The MM5‐VIC model reproduced the key features of NAMS in 1984 and 1989 especially over northwestern Mexico. Our modeling results indicate that the land surface has memory of the initial soil wetness prescribed at the onset of the monsoon that persists over most of the region well into the monsoon season (e.g. until August). However, in contrast to the classical thermal contrast concept, where wetter soils lead to cooler surface temperatures, less land‐sea thermal contrast, weaker monsoon circulations and less precipitation, the coupled model consistently demonstrated a positive soil moisture – precipitation feedback. Specifically, anomalously wet pre‐monsoon soil moisture always lead to enhanced monsoon precipitation, and the reverse was also true. Both the large‐scale circulation change and local land‐atmospheric interactions in response to pre‐monsoon soil moisture anomalies play important roles in the coupled model's positive soil moisture – monsoon precipitation feedback. However, the former may be sensitive to the strength and location of the thermal anomalies, thus leaving open the possibility of both positive and negative soil moisture – precipitation feedbacks. Furthermore, our use of a regional model with prescribed large‐scale circulation at the model boundaries leaves open the possibility that the model behavior may, to some extent, reflect its limited ability to adjust its large‐scale circulation to the regional thermal changes.

A scaling analysis of soil moisture–precipitation interactions in a regional climate model

The University of Oklahoma’s Advanced Regional Prediction System (ARPS) was used to examine the impacts of varying mean soil moisture and model resolution on the magnitude and frequency of precipitation events in the U.S. Central Plains and to determine whether modeled soil moisture and precipitation fields exhibit scale invariance using the statistical moments. It was found that high soil moisture resulted in greater precipitation amounts and a higher frequency of events, suggesting the occurrence of a positive soil moisture–precipitation feedback. The scaling analysis performed on cumulative precipitation determined that these fields did not exhibit signs of self-similarity and, therefore, statistical properties cannot be predicted at other resolutions. The scaling properties of soil moisture were highly variable in time which has important implications for the use of remotely sensed data, as scaling properties from 1 day cannot necessarily be applied to subsequent days.

Assessing land‐atmosphere coupling using soil moisture from the Global Land Data Assimilation System and observational precipitation

Precipitation analysis and soil moisture from the Global Land Data Assimilation System (GLDAS) are used to assess the land‐atmosphere coupling in boreal summer. Correlations between antecedent soil moisture and precipitation suggest that regions of strong land‐atmosphere coupling lie mainly in arid to semiarid transition zones or in semihumid forest to grassland transition zones. They consist of central Eurasia, the region from Mongolia to northern China, southwest China, the Sahel, the northern continental United States, and southern Europe. It is found that over these regions, positive soil moisture feedback accounts for typically 10–20% of the variance of monthly precipitation anomalies with the feedback efficiency of the order of 0.3–0.9 mm month−1 (0.1 standardized soil moisture)−1. While soil moisture feedback is dominated by the positive sign, negative feedback may exist in some areas, such as India and the western part and Quebec province of Canada. Generally, the land‐atmosphere coupling strength estimated from the GLDAS data agrees well with those from the observational soil moisture in Illinois and the European Centre for Medium‐Range Weather Forecasts 40‐year reanalysis (ERA‐40) soil moisture product. Physical mechanisms responsible for the findings are further discussed. This study provides a Northern Hemisphere distribution of the land‐atmosphere coupling strength, which can be used to test the model simulations on monthly to seasonal time scales.

Statistical identification of global hot spots in soil moisture feedbacks among IPCC AR4 models

Soil moisture feedbacks can regulate climate change and offer the potential for seasonal climate predictability, yet their strengths and regional importance are poorly understood. A statistical analysis of soil moisture feedbacks on boreal and austral summer precipitation is performed using output from 19 climate models in the Intergovernmental Panel on Climate Change's Fourth Assessment Report. The methodology, using lagged covariance ratios, was previously applied to study ocean‐atmosphere and vegetation‐atmosphere interactions. Reflecting ensemble‐based findings from the Global Land‐Atmosphere Coupling Experiment (GLACE) for boreal summer, positive soil moisture feedback hot spots are identified over central United States, North Africa, India, northern Brazil, and western Eurasia. Hot spots for austral summer include the Amazon, Congo, Australia, Indonesia, Mexico, and southwest United States. This statistical approach focuses on appropriate spatial and temporal scales of interaction, quantifies local feedbacks with significance testing, and expedites a reliable model intercomparison of feedbacks, without producing additional dynamical experiments.

Global Trends and Variability in Soil Moisture and Drought Characteristics, 1950–2000, from Observation-Driven Simulations of the Terrestrial Hydrologic Cycle

Abstract Global and regional trends in drought for 1950–2000 are analyzed using a soil moisture–based drought index over global terrestrial areas, excluding Greenland and Antarctica. The soil moisture fields are derived from a simulation of the terrestrial hydrologic cycle driven by a hybrid reanalysis–observation forcing dataset. Drought is described in terms of various statistics that summarize drought duration, intensity, and severity. There is an overall small wetting trend in global soil moisture, forced by increasing precipitation, which is weighted by positive soil moisture trends over the Western Hemisphere and especially in North America. Regional variation is nevertheless apparent, and significant drying over West Africa, as driven by decreasing Sahel precipitation, stands out. Elsewhere, Europe appears to have not experienced significant changes in soil moisture, a trait shared by Southeast and southern Asia. Trends in drought duration, intensity, and severity are predominantly decreasing, but statistically significant changes are limited in areal extent, of the order of 1.0%–7.0% globally, depending on the variable and drought threshold, and are generally less than 10% of continental areas. Concurrent changes in drought spatial extent are evident, with a global decreasing trend of between −0.021% and −0.035% yr−1. Regionally, drought spatial extent over Africa has increased and is dominated by large increases over West Africa. Northern and East Asia show positive trends, and central Asia and the Tibetan Plateau show decreasing trends. In South Asia all trends are insignificant. Drought extent over Australia has decreased. Over the Americas, trends are uniformly negative and mostly significant. Within the long-term trends there are considerable interannual and decadal variations in soil moisture and drought characteristics for most regions, which impact the robustness of the trends. Analysis of detrended and smoothed soil moisture time series reveals that the leading modes of variability are associated with sea surface temperatures, primarily in the equatorial Pacific and secondarily in the North Atlantic. Despite the overall wetting trend there is a switch since the 1970s to a drying trend, globally and in many regions, especially in high northern latitudes. This is shown to be caused, in part, by concurrent increasing temperatures. Although drought is driven primarily by variability in precipitation, projected continuation of temperature increases during the twenty-first century indicate the potential for enhanced drought occurrence.

Impact of Vegetation Feedback on the Response of Precipitation to Antecedent Soil Moisture Anomalies over North America

Abstract Previous studies support a positive soil moisture–precipitation feedback over a major fraction of North America; that is, initial soil moisture anomalies lead to precipitation anomalies of the same sign. To investigate how vegetation feedback modifies the sensitivity of precipitation to initial soil moisture conditions over North America, a series of ensemble simulations are carried out using a modified version of the coupled Community Atmosphere Model–Community Land Model (CAM–CLM). The modified CLM includes a predictive vegetation phenology scheme so that the coupled model can represent interactions between soil moisture, vegetation, and precipitation at the seasonal time scale. The focus of this study is on how the impact of vegetation feedback varies with the timing and direction of initial soil moisture anomalies. During summer, wet soil moisture anomalies lead to increase in leaf area index and, consequently, increase in evapotranspiration and surface heating. Such increases tend to favor precipitation. Therefore, under wet summer soil moisture anomalies, the soil moisture–induced precipitation increase is reinforced when predictive phenology is included. That is, the vegetation feedback to precipitation is positive. The response of vegetation to dry soil moisture anomalies in the summer months, however, is not significant due probably to a dry bias in the model, so the resulting vegetation feedback on precipitation is minimal. To soil moisture anomalies in spring, the leaf area index (LAI) response is delayed since LAI is still limited by cold temperature at that time of the year. During the summer following wet spring soil moisture anomalies, vegetation feedback is negative; that is, it tends to suppress the response of precipitation through the depletion of soil moisture by vegetation.

Global warming affect Collembola community: A long-term study

Summary Long-term (1992–2002) effects of climate changes on soil Collembola in Scots pine Pinus sylvestris forests in North Vidzeme Biosphere Reserve (northern Latvia) are investigated. The study was carried out in three forest stands of different age, young (30–40 years), middle aged (50–70 years), and old (150–200 years). One hundred soil samples were collected within each sampling site once a year in autumn over a period of 11 years. In total, 66 species of Collembola were found. Species richness varied between 47 and 56 and density of Collembola from 7300 to 8300 ind m−2. A statistically significant increase in the sums of positive air temperatures (⩾4 °C) was recorded during the period of investigation. Precipitation and thereby soil moisture showed considerable year-to-year fluctuations. Non-metric Multidimensional Scaling of the data yielded two axes explaining 48.6% and 38.6% of the variation. Axis 1 coincided with the trend of sums of positive air temperature ( r = 0.66 ). Axis 1 corresponded best with the negative impact of warming of climate on Collembola, mainly on the euedaphic species inhabiting the deeper layers of the organic soil horizon. Axis 2 was considered reflecting the effect of soil moisture fluctuations (correlation with moisture r = - 0.62 ) on litter dwelling, mostly hemiedaphic Collembola. Species richness tended to decrease gradually in all forest sites during the study period from 29–36 to 13–26 species. Correlation between axes ( r = 0.455 ) indicated interaction effects between positive air temperatures and soil moisture. Forest age showed no substantial effect on the community structure, therefore the changes observed cannot be explained by ecological succession.

Forty‐five years of observed soil moisture in the Ukraine: No summer desiccation (yet)

We present the longest data set of observed soil moisture available in the world, 45 yr of gravimetrically‐observed plant available soil moisture for the top 1 m of soil, observed every 10 days for April–October for 141 stations from fields with either winter or spring cereals from the Ukraine for 1958–2002. We averaged the summer observations over the entire region to account for the observed scale of soil moisture variations, to enhance the portion of the variance that is related to meteorological forcing. The observations show a positive soil moisture trend for the entire period of observation, with the trend leveling off in the last two decades. Although models of global warming predict summer desiccation in a greenhouse‐warmed world, there is no evidence for this in the observations yet, even though the region has been warming for the entire period. While the interannual variations of soil moisture simulated by both the European Centre for Medium‐range Weather Prediction and the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalyses are close to the observations, neither reanalysis simulates the observed upward trend. Climate model simulations for the period show the same general shape as the observations, but differ quite a bit from each other and from the observations. An observed downward trend in insolation may have produced a downward trend in evaporation and may have contributed to the upward soil moisture trend.

The Effects of Satellite-Derived Vegetation Cover Variability on Simulated Land–Atmosphere Interactions in the NAMS

Abstract Substantial evolution of Normalized Difference Vegetation Index (NVDI)-derived vegetation cover (Fg) exists in the southwestern United States and Mexico. The intraseasonal and wet-/dry-year fluctuations of Fg are linked to observed precipitation in the North American monsoon system (NAMS). The manner in which the spatial and temporal variability of Fg influences the land–atmosphere energy and moisture fluxes, and associated likelihood of moist convection in the NAMS regions, is examined. For this, the regional climate model (RCM) is employed, with three different Fg boundary conditions to examine the influence of intraseasonal and wet-/dry-year vegetation variability. Results show that a strong link exists between evaporative fraction (EF), surface temperature, and relative humidity in the boundary layer (BL), which is consistent with a positive soil moisture feedback. However, contrary to expectations, higher Fg does not consistently enhance EF across the NAMS region. This is because the low soil moisture values simulated by the land surface model (LSM) yield high canopy resistance values throughout the monsoon season. As a result, the experiment with the lowest Fg yields the greatest EF and precipitation in the NAMS region, and also modulates regional atmospheric circulation that steers the track of tropical cyclones. In conclusion, the simulated influence of vegetation on land–atmosphere exchanges depends strongly on the canopy stress index parameterized in the LSM. Therefore, a reliable dataset, at appropriate scales, is needed to calibrate transpiration schemes and to assess simulated and realistic vegetation–atmosphere interactions in the NAMS region.

Preliminary study of spin‐up processes in land surface models with the first stage data of Project for Intercomparison of Land Surface Parameterization Schemes Phase 1(a)

The spin‐up of a land surface model (LSM) is broadly defined as an adjustment process as the model approaches its equilibrium following initial anomalies in soil moisture content or after some abnormal environmental forcings (e.g., drought). The spin‐up timescale of LSMs has received little attention in the modeling community. This study uses results from Phase 1(a) of the Project for Intercomparison of Land Surface Parameterization Schemes, and finds that most land surface schemes require many years to come to thermal and hydrologic equilibrium with the forcing meteorology; the time needed depends on the total moisture holding capacity and the initialization of the moisture stores. The linear relationship established for bucket‐type models is just a special case of that found for the more sophisticated nonbucket‐type models, at least when the models start out with adequate soil moisture. When soil moisture begins at zero or when precipitation is set to zero, there is a nonlinear relationship. Sensitivity studies using the Biosphere‐Atmosphere Transfer Scheme confirm that precipitation intensity, solar radiation forcing, vegetation cover, and stomatal resistance also affect the length of spin‐up time. The results underline that the accurate calculation of precipitation and solar radiation incident at the Earth's surface is important for a realistic simulation of soil moisture content. Magnitudes of simulated heat fluxes at equilibrium are not related to the thickness of the soil layer below the rooting zone. For most LSMs, initial positive soil moisture anomalies are associated with initial positive evapotranspiration (E) anomalies, while initial negative anomalies of soil moisture are accompanied by the initial negative, but much stronger, E anomalies, as found in past studies performed with general circulation models. In addition, the implications of the spin‐up for numerical weather prediction and climate simulation are discussed.