A global evaluation of IMERG precipitation occurrence using SMAP detected soil moisture change

2021 ◽  
Keyword(s):  
Soil Moisture ◽  
Contingency Table ◽  
Global Scale ◽  
Global Evaluation ◽  
Validation Method ◽  
Precipitation Occurrence ◽  
Novel Approach ◽  
Skill Scores ◽  
Ground Validation ◽  
Global Mean

Abstract A globally consistent ground validation method for remotely sensed precipitation products is crucial for building confidence in these products. This study develops a new methodology to validate the IMERG precipitation products through the use of SMAP soil moisture changes as a proxy for precipitation occurrence. Using a standard 2x2 contingency table method, preliminary results provide confidence in SMAP’s ability to be utilized as a validation tool for IMERG as results are comparable to previous validation studies. However, the method allows for an overestimate of false alarm frequency due to light precipitation events that can evaporate before the subsequent SMAP overpass and changes in overpass-to-overpass SMAP soil moisture that are within the range of SMAP uncertainty. To counter these issues, a 3x3 contingency table is used to reduce noise and extract more signal from the detection method. Through the use of this novel approach, the validation method produces a global mean POD of 0.64 and global mean FAR of 0.40, the first global-scale ground validation skill scores for the IMERG products. Advancing the method to validate precipitation quantity and the development of a real-time validation for the IMERG Early product are the crucial next developments.

scholarly journals On the utility of land surface models for agricultural drought monitoring

2012 ◽  
Vol 16 (9) ◽  
pp. 3451-3460 ◽  
Author(s):  
W. T. Crow ◽  
S. V. Kumar ◽  
J. D. Bolten
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Cross Correlation ◽  
Root Zone ◽  
Vegetation Indices ◽  
Agricultural Drought ◽  
Drought Monitoring ◽  
Global Evaluation ◽  
Land Surface Models ◽  
Surface Models

Abstract. The lagged rank cross-correlation between model-derived root-zone soil moisture estimates and remotely sensed vegetation indices (VI) is examined between January 2000 and December 2010 to quantify the skill of various soil moisture models for agricultural drought monitoring. Examined modeling strategies range from a simple antecedent precipitation index to the application of modern land surface models (LSMs) based on complex water and energy balance formulations. A quasi-global evaluation of lagged VI/soil moisture cross-correlation suggests, when globally averaged across the entire annual cycle, soil moisture estimates obtained from complex LSMs provide little added skill (< 5% in relative terms) in anticipating variations in vegetation condition relative to a simplified water accounting procedure based solely on observed precipitation. However, larger amounts of added skill (5–15% in relative terms) can be identified when focusing exclusively on the extra-tropical growing season and/or utilizing soil moisture values acquired by averaging across a multi-model ensemble.

SOURCES OF GLOBAL SCALE SOIL MOISTURE MONITORING DATA BY SATELLITE BASED REMOTE SENSING OF EARTH’S SURFACE

2021 ◽  
Vol 100 (1) ◽  
pp. 36-41
Author(s):  
A.A. Volchek ◽  
◽  
D.O. Petrov ◽  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Global Scale ◽  
Research Papers ◽  
Equivalent Thickness ◽  
Satellite Gravimetry ◽  
Volumetric Soil Moisture ◽  
Characteristic Features ◽  
Agricultural Regions ◽  
Land Water

A review of modern tools of global monitoring of soil moisture by means of remote sensing of the Earth’s surface is presented. The characteristic features of the use of orbital radiometers and radars of C, X and L microwave bands for estimating the volumetric soil moisture at a depth of 5 cm and the root layer of vegetation are considered. A review of the capabilities of satellite gravimetry to assess the land water equivalent thickness is made. A number of sources have been proposed for obtaining estimates of soil water content from satellite based radiometric devices and orbital gravimetric systems. Based on the analysis of scientific research papers, the complexity of monitoring the level of fire danger indices in forests is shown, and the prospects of assessing soil moisture in agricultural regions using microwave orbital instruments are demonstrated, and the adequacy of calculating the moisture content in soil at a depth of up to one meter using satellite gravimetry is described.

scholarly journals The relationship between aerosol and cloud drop number concentrations in a global aerosol microphysics model

2009 ◽  
Vol 9 (1) ◽  
pp. 3207-3241 ◽  
Author(s):  
K. J. Pringle ◽  
K. S. Carslaw ◽  
D. V. Spracklen ◽  
G. M. Mann ◽  
M. P. Chipperfield
Keyword(s):  
Size Distribution ◽  
Cloud Droplet ◽  
Global Scale ◽  
Rate Of Change ◽  
The Arctic ◽  
Aerosol Size Distribution ◽  
Percentage Error ◽  
Empirical Relationships ◽  
Wide Range ◽  
Global Mean

Abstract. Empirical relationships that link cloud droplet number (CDN) to aerosol number or mass are commonly used to calculate global fields of CDN for climate forcing assessments. In this work we use a sectional global model of sulfate and sea-salt aerosol coupled to a mechanistic aerosol activation scheme to explore the limitations of this approach. We find that a given aerosol number concentration produces a wide range of CDN concentrations due to variations in the shape of the aerosol size distribution. On a global scale, the dependence of CDN on the size distribution results in regional biases in predicted CDN (for a given aerosol number). Empirical relationships between aerosol number and CDN are often derived from regional data but applied to the entire globe. In an analogous process, we derive regional "correlation-relations" between aerosol number and CDN and apply these regional relations to calculations of CDN on the global scale. The global mean percentage error in CDN caused by using regionally derived CDN-aerosol relations is 20 to 26%, which is about half the global mean percentage change in CDN caused by doubling the updraft velocity. However, the error is as much as 25–75% in the Southern Ocean, the Arctic and regions of persistent stratocumulus when an aerosol-CDN correlation relation from the North Atlantic is used. These regions produce much higher CDN concentrations (for a given aerosol number) than predicted by the globally uniform empirical relations. CDN-aerosol number relations from different regions also show very different sensitivity to changing aerosol. The magnitude of the rate of change of CDN with particle number, a measure of the aerosol efficacy, varies by a factor 4. CDN in cloud processed regions of persistent stratocumulus is particularly sensitive to changing aerosol number. It is therefore likely that the indirect effect will be underestimated in these important regions.

scholarly journals Landslide susceptibility mapping on a global scale using the method of logistic regression

2017 ◽  
Vol 17 (8) ◽  
pp. 1411-1424 ◽  
Author(s):  
Le Lin ◽  
Qigen Lin ◽  
Ying Wang
Keyword(s):  
Logistic Regression ◽  
Soil Moisture ◽  
Landslide Susceptibility ◽  
Confusion Matrix ◽  
Area Under The Curve ◽  
Global Scale ◽  
Landslide Susceptibility Mapping ◽  
Landslide Occurrence ◽  
Explanatory Factors ◽  
Five Factors

Abstract. This paper proposes a statistical model for mapping global landslide susceptibility based on logistic regression. After investigating explanatory factors for landslides in the existing literature, five factors were selected for model landslide susceptibility: relative relief, extreme precipitation, lithology, ground motion and soil moisture. When building the model, 70 % of landslide and nonlandslide points were randomly selected for logistic regression, and the others were used for model validation. To evaluate the accuracy of predictive models, this paper adopts several criteria including a receiver operating characteristic (ROC) curve method. Logistic regression experiments found all five factors to be significant in explaining landslide occurrence on a global scale. During the modeling process, percentage correct in confusion matrix of landslide classification was approximately 80 % and the area under the curve (AUC) was nearly 0.87. During the validation process, the above statistics were about 81 % and 0.88, respectively. Such a result indicates that the model has strong robustness and stable performance. This model found that at a global scale, soil moisture can be dominant in the occurrence of landslides and topographic factor may be secondary.

Predictability of U.S. Regional Extreme Precipitation Occurrence Based on Large-Scale Meteorological Patterns (LSMPs)

2021 ◽  
pp. 1-61
Author(s):  
Xiang Gao ◽  
Shray Mathur
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Warm Season ◽  
Prediction Skill ◽  
Large Set ◽  
Synoptic Scale ◽  
Potential Predictability ◽  
Precipitation Occurrence ◽  
Skill Scores ◽  
Analogue Method

AbstractIn this study, we use analogue method and Convolutional Neural Networks (CNNs) to assess the potential predictability of extreme precipitation occurrence based on Large-Scale Meteorological Patterns (LSMPs) for the winter (DJF) of Pacific Coast California (PCCA) and the summer (JJA) of Midwestern United States (MWST). We evaluate the LSMPs constructed with a large set of variables at multiple atmospheric levels and quantify the prediction skill with a variety of complementary performance measures. Our results suggest that LSMPs provide useful predictability of daily extreme precipitation occurrence and its interannual variability over both regions. The 14-year (2006-2019) independent forecast shows Gilbert Skill Scores (GSS) in PCCA range from 0.06 to 0.32 across 24 CNN schemes and from 0.16 to 0.26 across 4 analogue schemes, in contrast to those from 0.1 to 0.24 and from 0.1 to 0.14 in MWST. Overall, CNN is shown to be more powerful in extracting the relevant features associated with extreme precipitation from the LSMPs than analogue method, with several single-variate CNN schemes achieving more skillful prediction than the best multi-variate analogue scheme in PCCA and more than half of CNN schemes in MWST. Nevertheless, both methods highlight the Integrated Vapor Transport (IVT, or its zonal and meridional components) enables higher skills than other atmospheric variables over both regions. Warm-season extreme precipitation in MWST presents a forecast challenge with overall lower prediction skill than in PCCA, attributed to the weak synoptic-scale forcing in summer.

The CIMR mission and its unique capabilities for soil moisture sensing

2021 ◽  
Author(s):  
Maria Piles ◽  
Roberto Fernandez-Moran ◽  
Luis Gómez-Chova ◽  
Gustau Camps-Valls ◽  
Dara Entekhabi ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Spatial Scales ◽  
Microwave Radiometer ◽  
Critical Time ◽  
Global Scale ◽  
The Arctic ◽  
Temporal Perspective ◽  
Microwave Radiometers ◽  
Moisture Sensing

&lt;p&gt;The Copernicus Imaging Microwave Radiometer (CIMR) mission is currently being developed as a High Priority Copernicus Mission to support the Integrated European Policy for the Arctic. Due to its measurement characteristics, CIMR has exciting capabilities to enable a unique set of land surface products and science applications at a global scale. These characteristics go beyond what previous microwave radiometers (e.g. AMSR series, SMAP and SMOS) provide, and therefore allow for entirely new approaches to the estimation of bio-geophysical products from brightness temperature observations. Most notably, CIMR channels (L-,C-,X-,Ka-,Ku-bands) are very well fit for the simultaneous retrieval of soil moisture and vegetation properties, like biomass and moisture of different plant components such as leaves, stems or trunks. Also, the distinct spatial resolution of each frequency band allows for the development of approaches to cascade information and obtain these properties at multiple spatial scales. From a temporal perspective, CIMR has a higher revisit time than previous L-band missions dedicated to soil moisture monitoring (about 1 day global, sub-daily at the poles). This improved temporal resolution could allow resolving critical time scales of water processes, which is relevant to better model and understand land-atmosphere exchanges and feedbacks. In this presentation, new opportunities for soil moisture remote sensing made possible by the CIMR mission, as well as synergies and cross-sensor opportunities will be discussed.&amp;#160;&amp;#160;&lt;/p&gt;

Modelling Thousands of Fractures Using Analytic Elements

2021 ◽  
Author(s):  
Erik Toller ◽  
Otto Strack
Keyword(s):  
Exact Solution ◽  
Plane Strain ◽  
Numerical Models ◽  
Element Model ◽  
Global Scale ◽  
Hydraulic Fractures ◽  
Infinite Domain ◽  
Novel Approach ◽  
Analytic Elements ◽  
Kolosov Functions

&lt;p&gt;Understanding and modelling hydraulic fractures and fracture networks have a fundamental role in mapping the mechanical behaviour of rocks. A problem arises in the discontinuous behaviour of the fractures and how to accurately and efficiently model this. We present a novel approach for modelling many cracks randomly using analytic elements placed under plane strain conditions in an elastic medium. The analytic elements allow us to model the assembly computationally efficiently and up to machine precision. The crack element is the first step in the development of a model suitable for investigating the effect of fissures on tunnels in rock. The model can be used to validate numerical models and more.The solution for a single hydraulic pressurized crack in an infinite domain in plane strain was initially developed by Griffith (1921). We demonstrate that it is possible, by using series expansions in terms of complex variables, based on the Muskhelisvili-Kolosov functions, to generalize this solution to the case of an assembly of non-intersecting pressurized cracks. The solution consists of infinite series for each element Strack &amp; Toller (2020). The expressions for the displacements and stress tensor components approach the exact solution, as the number of terms in the series approaches infinity.We present the case where two cracks approach each other orthogonally to less than 1/2000th of the cracks length. We show the effect of increasing the number of terms in the expansion and how this influences the precision, demonstrating that the result approaches the exact solution. We also present a case with 10,000 cracks; the coefficients are determined using an iterative solver. By using analytic elements, we can both present the corresponding stress and deformations field for the global scale and for small scales in the close proximity of individual cracks.ReferencesGriffith, A. A. (1921). The phenomena of rupture and &amp;#64258;ow in solids. Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character, 221(582-593):163&amp;#8211;198.Strack, O. D. L. and Toller, E. A. L. (2020). An analytic element model for highly fractured elastic media, manuscript submitted for publication in International Journal for Numerical and Analytical Methods in Geomechanics.&lt;/p&gt;

GlacierMIP3 global glacier mass change equilibration experiments - rationale and experimental design

2021 ◽  
Author(s):  
Harry Zekollari ◽  
Regine Hock ◽  
Ben Marzeion ◽  
Fabien Maussion ◽  
Lilian Schuster ◽  
...  
Keyword(s):  
Experimental Design ◽  
Sea Level ◽  
Ice Sheets ◽  
Global Scale ◽  
Mass Change ◽  
Glacier Mass Balance ◽  
Model Intercomparison ◽  
Climate Conditions ◽  
Equilibrium Volume ◽  
Global Mean

&lt;p&gt;Glaciers outside the ice sheets are major contributors to today&amp;#8217;s sea-level rise and are projected to remain so in the coming century. With the goal to better assess the future sea-level contribution from glaciers and to quantify related uncertainties, the Glacier Model Intercomparison Project (GlacierMIP) has set out to develop a series of coordinated experiments to be run as a community-wide effort.&lt;/p&gt;&lt;p&gt;The first two phases of the GlacierMIP have focused on the evolution of glaciers throughout the 21&lt;sup&gt;st&lt;/sup&gt; century (Hock et al., 2019; Marzeion et al., 2020). In the third phase of GlacierMIP (GlacierMIP3 &amp;#8211; equilibration), a new set of experiments has been designed to investigate the equilibration of glaciers under constant climate conditions. These experiments will allow us to answer the following fundamental questions:&lt;/p&gt;&lt;p&gt;1. What would be the equilibrium volume and area of all glaciers outside the ice sheets if global mean temperatures were to stabilize at present-day levels?&lt;/p&gt;&lt;p&gt;2. What would be the equilibrium volume and area of all glaciers outside the ice sheets if global mean temperatures were to stabilize at different temperature levels (e.g. +1.5, +2, relative to pre-industrial)?&lt;/p&gt;&lt;p&gt;3. For each of these global mean temperature stabilization scenarios, how much time would the glaciers need to reach their new equilibrium?&lt;/p&gt;&lt;p&gt;In this contribution, we present the experimental design of GlacierMIP3 and open up the floor for ideas and discussions about possible processing of these experiments. We also invite interested individuals and groups to join us to discuss the possibility of their model to be included in the newest phase of GlacierMIP.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;GlacierMIP1&lt;/strong&gt;: Hock, R., Bliss, A., Marzeion, B., Giesen, R.H., Hirabayashi, Y., Huss, M., Radic, V., Slangen, A.B.A. (2019), GlacierMIP &amp;#8211; A model intercomparison of global-scale glacier mass-balance models and projections, Journal of Glaciology 65(251), 453-467, doi: 10.1017/jog.2019.22&lt;/p&gt;&lt;p&gt;&lt;strong&gt;GlacierMIP2&lt;/strong&gt;: Marzeion, B., Hock, R., Anderson, B., Bliss, A., Champollion, N., Fujita, K., Huss, M., Immerzeel, W., Kraaijenbrink, P., Malles, J-H., Maussion, F., Radic, V., Rounce, D.R., Sakai, A., Shannon, S., van de Wal, R., Zekollari, H. (2020), Partitioning the Uncertainty of Ensemble Projections of Global Glacier Mass Change, Earth&amp;#8217;s Future 8(7), e2019EF001470, doi: 10.1029/2019EF001470&lt;/p&gt;

Case Study on WSN Based Smart Home Garden with Priority Driven Approach

2020 ◽  
pp. 945-958
Author(s):  
Santosh R. Durugkar ◽  
Ramesh C. Poonia ◽  
Radhakrishna B. Naik
Keyword(s):  
Soil Moisture ◽  
Wireless Sensor Network ◽  
Wireless Sensor ◽  
Large Field ◽  
Home Garden ◽  
Critical Factors ◽  
New Era ◽  
Novel Approach ◽  
Quality Water

The proposed system focuses on utilizing the available water for a home garden in an effective way. The same approach is applicable to agriculture (large field), as our country's economy depends up on the agriculture. Therefore, agriculture is the backbone of Indian economy. In this paper, the authors have proposed a novel approach priority driven scheduling based irrigation model (for home garden) which supplies optimum and good quality water to the crops. The most important part for such system is Wireless Sensor Network which irrigates the plants. The proposed system will be very useful as it immediately irrigates the plant. In this process, soil moisture values will be sensed and compared to find out the lowest value. It means water will be given immediately to such plants where moisture values are low. Such systems will start new era in agriculture and will prove itself as a major requirement in the future due to many critical factors such as irregularity of monsoon, less availability of water, etc.

Case Study on WSN Based Smart Home Garden with Priority Driven Approach

2017 ◽  
Vol 19 (4) ◽  
pp. 37-48 ◽  
Author(s):  
Santosh R. Durugkar ◽  
Ramesh C. Poonia ◽  
Radhakrishna B. Naik
Keyword(s):  
Soil Moisture ◽  
Smart Home ◽  
Wireless Sensor ◽  
Large Field ◽  
Home Garden ◽  
Critical Factors ◽  
New Era ◽  
Novel Approach ◽  
Quality Water

The proposed system focuses on utilizing the available water for a home garden in an effective way. The same approach is applicable to agriculture (large field), as our country's economy depends up on the agriculture. Therefore, agriculture is the backbone of Indian economy. In this paper, the authors have proposed a novel approach priority driven scheduling based irrigation model (for home garden) which supplies optimum and good quality water to the crops. The most important part for such system is Wireless Sensor Network which irrigates the plants. The proposed system will be very useful as it immediately irrigates the plant. In this process, soil moisture values will be sensed and compared to find out the lowest value. It means water will be given immediately to such plants where moisture values are low. Such systems will start new era in agriculture and will prove itself as a major requirement in the future due to many critical factors such as irregularity of monsoon, less availability of water, etc.

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