RESPONSES OF SOIL MOISTURE TO CLIMATE VARIABILITY AND LIVESTOCK GRAZING IN A SEMIARID EURASIAN STEPPE

As region that is highly sensitive to global climate change, the Tibetan Plateau (TP) experiences an intra-seasonal soil water deficient due to the reduced precipitation during the South Asia monsoon (SAM) break. Few studies have investigated the impact of the SAM break on TP ecological processes, although a number of studies have explored the effects of inter-annual and decadal climate variability. In this study, the response of vegetation activity to the SAM break was investigated. The data used are: (1) soil moisture from in situ, satellite remote sensing and data assimilation; and (2) the Normalized Difference Vegetation Index (NDVI) and Solar-Induced chlorophyll Fluorescence&#160;(SIF). We found that in the region impacted by SAM break, which is distributed in the central-eastern part of TP, photosynthesis become more active during the SAM break. And temporal variability in the photosynthesis of this region is controlled mainly by solar radiation variability and has little sensitivity to soil moisture. We adopted a diagnostic process-based modeling approach to examine the causes of enhanced plant activity during the SAM break on the central-eastern TP. Our analysis indicates that active photosynthetic behavior in the reduced precipitation is stimulated by increases in solar radiation absorbed and temperature. This study highlights the importance of sub-seasonal climate variability for characterizing the relationship between vegetation and climate.

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Relationships between climate variability, soil moisture, and Australian heatwaves

Journal of Geophysical Research Atmospheres ◽

10.1002/2015jd023592 ◽

2015 ◽

Vol 120 (16) ◽

pp. 8144-8164 ◽

Cited By ~ 54

Author(s):

Sarah E. Perkins ◽

Daniel Argüeso ◽

Christopher J. White

Keyword(s):

Soil Moisture ◽

Climate Variability

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"Partial area contribution" and "Overland flow discontinuity": from humid to arid hillslopes

10.5194/egusphere-egu2020-3059 ◽

2020 ◽

Author(s):

Hanoch Lavee

Keyword(s):

Soil Moisture ◽

Overland Flow ◽

Infiltration Rate ◽

Dead Sea ◽

Livestock Grazing ◽

Rainfall Simulation ◽

Arid Areas ◽

Shallow Subsurface ◽

Partial Area ◽

Semi Arid

In humid temperate areas, where infiltration rate and soil moisture are high the hillslopes are draining mainly via shallow subsurface flow. Overland flow is seldom generated on the very low parts of hillslopes when the soil is saturated up to the surface. This spatial pattern is known as &#8220;partial area contribution&#8221;.In contrary, in arid areas, where the soil moisture is hygroscopic most of the time, overland flow is generated not because of soil saturation conditions but only when rainfall intensity is higher than the infiltration rate.&#160;&#160;Nevertheless, we found a &#8220;partial area contribution&#8221; pattern in several arid and semi-arid areas due other controlling factors:<ol><li>In eastern Sinai, under rainfall simulation experiments on scree slopes, due to high spatial differences in the soil texture, runoff coefficient in the gullies was almost 100% while in the very permeable interfluves runoff wasn&#8217;t generated at all. Overland flow was generated, therefore, only in the gullies (Lavee ,1973; Yair & Lavee ,1976).</li> <li>In an instrumented experimental watershed in the Northern Negev, the specific overland flow yield from long plots ,extending from the divide to the slope base (around 60m in length), was consistently lower than the combined specific overland flow yield from the adjacent two short plots (around 30m in length), draining the upper and the lower sections of the hillslope, respectively. This means that the overland flow is discontinuous and at least part of the overland flow that was generated at the upper part of the hillslope infiltrated, in most overland flow events, into the soil, before reaching the slope base. In other words, only the lower part of the hillslope contributes, in most cases, overland flow to the channel. Such overland flow discontinuity is controlled by: 1. The typical short duration of rain showers in arid areas. As more than 80% of the rain showers last for less than 15 minutes, the total flow duration is usually shorter than the concentration time. 2. The spatial distribution of infiltration rate. In this case it was mainly the relatively high infiltration rate in the colluvial cover at the lower part of the hillslopes in part of the study area that absorbed large amount of the water flowing from the upper part of the hillslopes (Lavee, 1982; Yair & Lavee, 1985; Lavee & Yair, 1990).</li> <li>In an experimental project along a climatological transect, running from the Mediterranean climate near Jerusalem to the extreme arid climate near the Dead Sea, the main reason for the overland flow discontinuity, especially in the semi-arid area, was the mosaic pattern of &#8220;source patches&#8221;, on which overland flow was generated, and &#8220;sink patches&#8221;, in which at least part of the direct rain and the incoming overland flow infiltrated. This pattern is produced by different processes, mainly via the effect of vegetation, but also due to the effects of micro-topography, big stones, especially if they are partly embedded in the soil, and livestock grazing (Lavee & Poesen, 1991; Lavee et al., 1998; Stavi et al., 2008).</li> </ol>

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Elusive drought: uncertainty in observed trends and short- and long-term CMIP5 projections

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-9-13773-2012 ◽

2012 ◽

Vol 9 (12) ◽

pp. 13773-13803 ◽

Cited By ~ 2

Author(s):

B. Orlowsky ◽

S. I. Seneviratne

Keyword(s):

South Africa ◽

Soil Moisture ◽

Climate Variability ◽

Central America ◽

21St Century ◽

Economic Losses ◽

Drought Risk ◽

Dominant Source ◽

Internal Climate Variability ◽

The Mediterranean

Abstract. Recent years have seen a number of severe droughts in different regions around the world, causing agricultural and economic losses, famines and migration. Despite their devastating consequences, the Standardised Precipitation Index (SPI) of these events lies within the range of internal climate variability, which we estimate from simulations from the 5th phase of the Coupled Model Intercomparison Project (CMIP5). In terms of drought magnitude, regional trends of SPI over the last decades remain mostly inconclusive in observations and CMIP5 simulations, although Soil Moisture Anomalies (SMAs) in CMIP5 simulations hint at increased drought in a few regions (e.g. the Mediterranean, Central America/Mexico, the Amazon, North-East Brazil and South Africa). Also for the future, projections of meteorological (SPI) and agricultural (SMA) drought in CMIP5 display large uncertainties over all time frames, generally impeding trend detection. Analogue analyses of the frequencies rather than magnitudes of future drought display, however, more robust signal-to-noise ratios with detectable trends towards more frequent drought until the end of the 21st century in the Mediterranean, South Africa and Central America/Mexico. Other present-day hot spots are projected to become less drought-prone, or to display unsignificant changes in drought occurrence. A separation of different sources of uncertainty in drought projections reveals that for the near term, internal climate variability is the dominant source, while the formulation of Global Climate Models (GCMs) generally becomes the dominant source of uncertainty by the end of the 21st century, especially for agricultural (soil moisture) drought. In comparison, the uncertainty in Green-House Gas (GHG) concentrations scenarios is negligible for most regions. These findings stand in contrast to respective analyses for a heat wave indicator, for which GHG concentrations scenarios constitute the main source of uncertainty. Our results highlight the inherent difficulty of drought quantification and the uncertainty of drought projections. However, high uncertainty should not be equated with low drought risk, since potential scenarios include large drought increases in key agricultural and ecosystem regions.

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Application of climate data to predict pasture production

Proceedings of the New Zealand Grassland Association ◽

10.33584/jnzg.2008.70.2708 ◽

2008 ◽

pp. 145-151

Author(s):

I.C. Blair

Keyword(s):

Soil Moisture ◽

Climate Variability ◽

Pacific Decadal Oscillation ◽

Southern Oscillation Index ◽

Reliable Method ◽

Southern Oscillation ◽

Climate Data ◽

Pasture Production ◽

Production Models ◽

Soil Moisture Status

With increasing climate variability, a reliable method of estimating pasture growth has eluded farmers. Rain, temperature, evapotranspiration, radiation and soil moisture status are components which interact and affect pasture production. In 1992, soil moisture monitoring in Marlborough vineyards was extended to pasture. Keywords: soil moisture, pasture production, models, Southern Oscillation Index, Pacific Decadal Oscillation

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Overview of the CCI+SSS project

10.5194/egusphere-egu2020-7513 ◽

2020 ◽

Author(s):

Jacqueline Boutin ◽

Nicolas Reul ◽

Julia Koehler ◽

Adrien Martin ◽

Rafael Catany ◽

...

Keyword(s):

Remote Sensing ◽

Soil Moisture ◽

Climate Variability ◽

Satellite Data ◽

Water Cycle ◽

Global Ocean ◽

Variable Regions ◽

New Findings ◽

Band Radiometer

Sea Surface Salinity (SSS) is an Essential Climate Variable (ECV) that plays a fundamental role in the density-driven global ocean circulation, the water cycle, and climate. The satellite SSS observation from the Soil Moisture and Ocean Salinity (SMOS), Aquarius, and Soil Moisture Active Passive (SMAP) missions have provided an unprecedented opportunity to map SSS over the global ocean since 2010 at 40-150km scale with a revisit every 2 to 3 days. This observation capability has no historic precedent and has brought new findings concerning the monitoring of SSS variations related with climate variability such as El Ni&#241;o-Southern Oscillation, Indian Ocean Dipole, and Madden-Julian Oscillation, and the linkages of the ocean with different elements of the water cycle such as evaporation and precipitation and continental runoff. It has enhanced the understanding of various ocean processes such as tropical instability waves, Rossby waves, mesoscale eddies and related salt transport, salinity fronts, hurricane haline wake, river plume variability, cross-shelf exchanges. There are also emerging use of satellite SSS to study ocean biogeochemistry, e.g. linked to air-sea CO2 fluxes.Following the success of the initial oceanographic studies implementing this new variable, the European Space Agency (ESA) Climate Change Initiative CCI+SSS project (2018-2020) aims at generating improved calibrated global SSS fields over 10 years period (2010-2019) from all available satellite L-band radiometer measurements, extended at regional scale to 2002-2019 from C-band radiometer measurements. It fully exploits the ESA/Earth explorer SMOS mission complemented with SMAP and AQUARIUS satellite missions. The project gathers teams involved in earth observation remote sensing, in the validation of satellite data and in climate variability study. In this presentation, we will present the first CCI+SSS product released to the scientific community (https://catalogue.ceda.ac.uk/uuid/9ef0ebf847564c2eabe62cac4899ec41). The comparisons with in situ ground truth indicate much better performances than the ones obtained with a single satellite data product, with global rmsd against in situ references of 0.16 pss. Large scale interannual variability is successfully reproduced and SSS variability in very variable regions like the Bay of Bengale and in river plumes in the Atlantic Ocean is very satisfactory, confirming the usefulness of these products for scientific studies. Nevertheless we also identify some caveats that will be discussed as well as the ways envisaged to resolve part of them in the next version of the product to be delivered publicly in Summer 2020.The ESA CCI+SSS consortium gathers scientists and engineers from various European research institutes and companies (LOCEAN/IPSL, LOPS, University of Hamburg, NOC, ICM, ARGANS, ACRI-st, ODL) and is conducted in collaboration with US colleagues from NASA and Remote Sensing System.

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Impact of Indo-Pacific Climate Variability on Rice Productivity in Bihar, India

Sustainability ◽

10.3390/su12177023 ◽

2020 ◽

Vol 12 (17) ◽

pp. 7023 ◽

Cited By ~ 1

Author(s):

Netrananda Sahu ◽

Atul Saini ◽

Swadhin Behera ◽

Takahiro Sayama ◽

Sridhara Nayak ◽

...

Keyword(s):

Soil Moisture ◽

Climate Variability ◽

Southern Oscillation Index ◽

Partial Correlation ◽

Southern Oscillation ◽

Maximum Temperature ◽

Climate Indices ◽

Rice Productivity ◽

Pacific Climate Variability ◽

The Impact

The impact of Indo-Pacific climate variability in the South Asian region is very pronounced and their impact on agriculture is very important for the Indian subcontinent. In this study, rice productivity, climatic factors (Rainfall, Temperature and Soil Moisture) and associated major Indo-Pacific climate indices in Bihar were investigated. Bihar is one of the major rice-producing states of India and the role of climate variability and prevailing climate indices in six events (between 1991–2014) with severer than −10% rice productivity are analyzed. The Five-year moving average, Pearson’s Product Moment Correlation, Partial Correlation, Linear Regression Model, Mann Kendall Test, Sen’s Slope and some other important statistical techniques were used to understand the association between climatic variables and rice productivity. Pearson’s Product Moment Correlation provided an overview of the significant correlation between climate indices and rice productivity. Whereas, Partial Correlation provided the most refined results on it and among all the climate indices, Niño 3, Ocean Niño Index and Southern Oscillation Index are found highly associated with years having severer than −10% decline in rice productivity. Rainfall, temperature and soil moisture anomalies are analyzed to observe the importance of climate factors in rice productivity. Along with the lack of rainfall, lack of soil moisture and persistent above normal temperature (especially maximum temperature) are found to be the important factors in cases of severe loss in rice productivity. Observation of the dynamics of ocean-atmosphere coupling through the composite map shows the Pacific warming signals during the event years. The analysis revealed a negative (positive) correlation of rice productivity with the Niño 3 and Ocean Niño Index (Southern Oscillation Index).

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Soil Moisture and Climate Variability

10.13031/cc.2052122019 ◽

2015 ◽

Keyword(s):

Soil Moisture ◽

Climate Variability

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Positive and negative effects of livestock grazing on plant diversity of Mongolian nomadic pasturelands along a slope with soil moisture gradient

Grassland Science ◽

10.1111/j.1744-697x.2009.00147.x ◽

2009 ◽

Vol 55 (3) ◽

pp. 126-134 ◽

Cited By ~ 21

Author(s):

Noboru Fujita ◽

Narantsetsegiin Amartuvshin ◽

Yasuhiro Yamada ◽

Kiyoshi Matsui ◽

Shoko Sakai ◽

...

Keyword(s):

Soil Moisture ◽

Plant Diversity ◽

Moisture Gradient ◽

Livestock Grazing ◽

Negative Effects ◽

Soil Moisture Gradient

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Feedbacks of Vegetation on Summertime Climate Variability over the North American Grasslands. Part I: Statistical Analysis

Earth Interactions ◽

10.1175/ei196.1 ◽

2006 ◽

Vol 10 (17) ◽

pp. 1-27 ◽

Cited By ~ 15

Author(s):

Weile Wang ◽

Bruce T. Anderson ◽

Nathan Phillips ◽

Robert K. Kaufmann ◽

Christopher Potter ◽

...

Keyword(s):

Soil Moisture ◽

Climate Variability ◽

Time Scales ◽

North American ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Spectral Characteristics ◽

Growing Season ◽

Statistical Technique ◽

The North

Abstract Feedbacks of vegetation on summertime climate variability over the North American Grasslands are analyzed using the statistical technique of Granger causality. Results indicate that normalized difference vegetation index (NDVI) anomalies early in the growing season have a statistically measurable effect on precipitation and surface temperature later in summer. In particular, higher means and/or decreasing trends of NDVI anomalies tend to be followed by lower rainfall but higher temperatures during July through September. These results suggest that initially enhanced vegetation may deplete soil moisture faster than normal and thereby induce drier and warmer climate anomalies via the strong soil moisture–precipitation coupling in these regions. Consistent with this soil moisture–precipitation feedback mechanism, interactions between temperature and precipitation anomalies in this region indicate that moister and cooler conditions are also related to increases in precipitation during the preceding months. Because vegetation responds to soil moisture variations, interactions between vegetation and precipitation generate oscillations in NDVI anomalies at growing season time scales, which are identified in the temporal and the spectral characteristics of the precipitation–NDVI system. Spectral analysis of the precipitation–NDVI system also indicates that 1) long-term interactions (i.e., interannual and longer time scales) between the two anomalies tend to enhance one another, 2) short-term interactions (less than 2 months) tend to damp one another, and 3) intermediary-period interactions (4–8 months) are oscillatory. Together, these results support the hypothesis that vegetation may influence summertime climate variability via the land–atmosphere hydrological cycles over these semiarid grasslands.

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