scholarly journals The Polarimetric Sensitivity of SMAP-Reflectometry Signals to Crop Growth in the U.S. Corn Belt

2020 ◽  
Vol 12 (6) ◽  
pp. 1007
Author(s):  
Nereida Rodriguez-Alvarez ◽  
Sidharth Misra ◽  
Mary Morris
Keyword(s):  
United States ◽  
Soil Moisture ◽  
The United States ◽  
Crop Growth ◽  
Corn Belt ◽  
Retrieval Algorithm ◽  
Agricultural Crop ◽  
Crop Height ◽  
Crop Type ◽  
The Impact

Crop growth is an important parameter to monitor in order to obtain accurate remotely sensed estimates of soil moisture, as well as assessments of crop health, productivity, and quality commonly used in the agricultural industry. The Soil Moisture Active Passive (SMAP) mission has been collecting Global Positioning System (GPS) signals as they reflect off the Earth’s surface since August 2015. The L-band dual-polarization reflection measurements enable studies of the evolution of geophysical parameters during seasonal transitions. In this paper, we examine the sensitivity of SMAP-reflectometry signals to agricultural crop growth related characteristics: crop type, vegetation water content (VWC), crop height, and vegetation opacity (VOP). The study presented here focuses on the United States “Corn Belt,” where an extensive area is planted every year with mostly corn, soybean, and wheat. We explore the potential to generate regularly an alternate source of crop growth information independent of the data currently used in the soil moisture (SM) products developed with the SMAP mission. Our analysis explores the variability of the polarimetric ratio (PR), computed from the peak signals at V- and H-polarization, during the United States Corn Belt crop growing season in 2017. The approach facilitates the understanding of the evolution of the observed surfaces from bare soil to peak growth and the maturation of the crops until harvesting. We investigate the impact of SM on PR for low roughness scenes with low variability and considering each crop type independently. We analyze the sensitivity of PR to the selected crop height, VWC, VOP, and Normalized Differential Vegetation Index (NDVI) reference datasets. Finally, we discuss a possible path towards a retrieval algorithm based on Global Navigation Satellite System-Reflectometry (GNSS-R) measurements that could be used in combination with passive SMAP soil moisture algorithms to correct simultaneously for the VWC and SM effects on the electromagnetic signals.

scholarly journals The Impact of SMOS Soil Moisture Data Assimilation within the Operational Global Flood Awareness System (GloFAS)

2020 ◽  
Vol 12 (9) ◽  
pp. 1490 ◽  
Author(s):  
Calum Baugh ◽  
Patricia de Rosnay ◽  
Heather Lawrence ◽  
Toni Jurlina ◽  
Matthias Drusch ◽  
...  
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Data Assimilation ◽  
The United States ◽  
Streamflow Prediction ◽  
Soil Moisture Data ◽  
Skill Scores ◽  
High Flows ◽  
The Impact ◽  
Awareness System

In this study the impacts of Soil Moisture and Ocean Salinity (SMOS) soil moisture data assimilation upon the streamflow prediction of the operational Global Flood Awareness System (GloFAS) were investigated. Two GloFAS experiments were performed, one which used hydro-meteorological forcings produced with the assimilation of the SMOS data, the other using forcings which excluded the assimilation of the SMOS data. Both sets of experiment results were verified against streamflow observations in the United States and Australia. Skill scores were computed for each experiment against the observation datasets, the differences in the skill scores were used to identify where GloFAS skill may be affected by the assimilation of SMOS soil moisture data. In addition, a global assessment was made of the impact upon the 5th and 95th GloFAS flow percentiles to see how SMOS data assimilation affected low and high flows respectively. Results against in-situ observations found that GloFAS skill score was only affected by a small amount. At a global scale, the results showed a large impact on high flows in areas such as the Hudson Bay, central United States, the Sahel and Australia. There was no clear spatial trend to these differences as opposing signs occurred within close proximity to each other. Investigating the differences between the simulations at individual gauging stations showed that they often only occurred during a single flood event; for the remainder of the simulation period the experiments were almost identical. This suggests that SMOS data assimilation may affect the generation of surface runoff during high flow events, but may have less impact on baseflow generation during the remainder of the hydrograph. To further understand this, future work could assess the impact of SMOS data assimilation upon specific hydrological components such as surface and subsurface runoff.

scholarly journals Trends in OMI NO<sub>2</sub> observations over the United States: effects of emission control technology and the economic recession

2012 ◽  
Vol 12 (24) ◽  
pp. 12197-12209 ◽  
Author(s):  
A. R. Russell ◽  
L. C. Valin ◽  
R. C. Cohen
Keyword(s):  
United States ◽  
Power Plants ◽  
Economic Recession ◽  
The United States ◽  
Retrieval Algorithm ◽  
Vertical Column ◽  
Large Power ◽  
Mobile Sources ◽  
Light Duty Vehicle ◽  
The Impact

Abstract. Observations of tropospheric NO2 vertical column densities over the United States (US) for 2005–2011 are evaluated using the OMI Berkeley High Resolution (BEHR) retrieval algorithm. We assess changes in NO2 on day-of-week and interannual timescales to assess the impact of changes in emissions from mobile and non-mobile sources on the observed trends. We observe consistent decreases in cities across the US, with an average total reduction of 32 ± 7% across the 7 yr. Changes for large power plants have been more variable (−26 ± 12%) due to regionally-specific regulation policies. An increasing trend of 10–20% in background NO2 columns in the northwestern US is observed. We examine the impact of the economic recession on emissions and find that decreases in NO2 column densities over cities were moderate prior to the recession (−6 ± 5% yr−1), larger during the recession (−8 ± 5% yr−1), and then smaller after the recession (−3 ± 4% yr−1). Differences in the trends observed on weekdays and weekends indicate that prior to the economic recession, NO2 reductions were dominated by technological improvements to the light-duty vehicle fleet but that a decrease in diesel truck activity has contributed to emission reductions since the recession. We use the satellite observations to estimate a 34% decrease in NO2 from mobile sources in cities for 2005–2011 and use that value to infer changes in non-mobile sources. We find that reductions in NO2 from non-mobile sources in cities have been both more modest and more variable than NO2 reductions from mobile sources (−10 ± 13%).

scholarly journals Role of Soil Moisture Feedback in the Development of Extreme Summer Drought and Flood in the United States

2016 ◽  
Vol 17 (8) ◽  
pp. 2191-2207 ◽  
Author(s):  
Roop Saini ◽  
Guiling Wang ◽  
Jeremy S. Pal
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Large Scale ◽  
Climate Model ◽  
The United States ◽  
Summer Drought ◽  
Large Set ◽  
Drought And Flood ◽  
The Impact ◽  
Soil Moisture Feedback

Abstract This study tackles the contribution of soil moisture feedback to the development of extreme summer precipitation anomalies over the conterminous United States using a regional climate model. The model performs well in reproducing both the mean climate and extremes associated with drought and flood. A large set of experiments using the model are conducted that involve swapped initial soil moisture between flood and drought years using the 1988 and 2012 droughts and 1993 flood as examples. The starting time of these experiments includes 1 May (late spring) and 1 June (early summer). For all three years, the impact of 1 May soil moisture swapping is much weaker than the 1 June soil moisture swapping. In 1988 and 2012, replacing the 1 June soil moisture with that from 1993 reduces both the spatial extent and the severity of the simulated summer drought and heat. The impact is especially strong in 2012. In 1993, however, replacing the 1 June soil moisture with that from 1988 has little impact on precipitation. The contribution of soil moisture feedback to summer extremes is larger in 2012 than in 1988 and 1993. This may be because of the presence of strong anomalies in large-scale forcing in 1988 and 1993 that prohibit or favor precipitation, and the lack of such in 2012. This study demonstrates how the contribution of land–atmosphere feedback to the development of seasonal climate anomalies may vary from year to year and highlights its importance in the 2012 drought.

scholarly journals Impact of Sea Surface Temperature and Soil Moisture on Summer Precipitation in the United States Based on Observational Data

2011 ◽  
Vol 12 (5) ◽  
pp. 1086-1099 ◽  
Author(s):  
Rui Mei ◽  
Guiling Wang
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Correlation Analysis ◽  
Surface Temperature ◽  
Precipitation Amount ◽  
Summer Precipitation ◽  
The United States ◽  
Sea Surface ◽  
Precipitation Prediction ◽  
The Impact

Abstract This study examines the impact of sea surface temperature (SST) and soil moisture on summer precipitation over two regions of the United States (the upper Mississippi River basin and the Great Plains) based on data from observation and observation-forced model simulations (in the case of soil moisture). Results from SST–precipitation correlation analysis show that spatially averaged SST of identified oceanic areas are better predictors than derived SST patterns from the EOF analysis and that both predictors are strongly associated with the Pacific Ocean. Results from conditioned soil moisture–precipitation correlation analysis show that the impact of soil moisture on precipitation differs between the outer-quartiles years (with summer precipitation amount in the first and fourth quartiles) and inner-quartiles years (with summer precipitation amount in the second and third quartiles), and also between the high- and low-skill SST years (categorized according to the skill of SST-based precipitation prediction). Specifically, the soil moisture–precipitation feedback is more likely to be positive and significant in the outer-quartiles years and in the years when the skill of precipitation prediction based on SST alone is low. This study indicates that soil moisture should be included as a useful predictor in precipitation prediction, and the resulting improvement in prediction skills will be especially substantial during years of large precipitation anomalies. It also demonstrates the complexity of the impact of SST and soil moisture on precipitation, and underlines the important complementary roles both SST and soil moisture play in determining precipitation.

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