scholarly journals Monitoring Drought over the Conterminous United States Using MODIS and NCEP Reanalysis-2 Data

2010 ◽  
Vol 49 (8) ◽  
pp. 1665-1680 ◽  
Author(s):  
Yunjun Yao ◽  
Shunlin Liang ◽  
Qiming Qin ◽  
Kaicun Wang
Keyword(s):  
United States ◽  
Spatial Resolution ◽  
Great Plains ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Moisture Stress ◽  
Ncep Reanalysis ◽  
Southern Great Plains ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract Monitoring land surface drought using remote sensing data is a challenge, although a few methods are available. Evapotranspiration (ET) is a valuable indicator linked to land drought status and plays an important role in surface drought detection at continental and global scales. In this study, the evaporative drought index (EDI), based on the estimated actual ET and potential ET (PET), is described to characterize the surface drought conditions. Daily actual ET at 4-km resolution for April–September 2003–05 across the continental United States is estimated using a simple improved ET model with input solar radiation acquired by Moderate-Resolution Imaging Spectroradiometer (MODIS) at a spatial resolution of 4 km and input meteorological parameters from NCEP Reanalysis-2 data at a spatial resolution of 32 km. The PET is also calculated using some of these data. The estimated actual ET has been rigorously validated with ground-measured ET at six Enhanced Facility sites in the Southern Great Plains (SGP) of the Atmosphere Radiation Measurement Program (ARM) and four AmeriFlux sites. The validation results show that the bias varies from −11.35 to 27.62 W m−2 and the correlation coefficient varies from 0.65 to 0.86. The monthly composites of EDI at 4-km resolution during April–September 2003–05 are found to be in good agreement with the Palmer Z index anomalies, but the advantage of EDI is its finer spatial resolution. The EDI described in this paper incorporates information about energy fluxes in response to soil moisture stress without requiring too many meteorological input parameters, and performs well in assessing drought at continental scales.

scholarly journals Variations in Winter Surface Temperature of the Purog Kangri Ice Field, Qinghai–Tibetan Plateau, 2001–2018, Using MODIS Data

2020 ◽  
Vol 12 (7) ◽  
pp. 1133
Author(s):  
Yufan Qie ◽  
Ninglian Wang ◽  
Yuwei Wu ◽  
An’an Chen
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Warming Trend ◽  
Data Set ◽  
Moderate Resolution ◽  
Ice Field ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Meteorological Observations

In the context of global warming, the land surface temperature (LST) from remote sensing data is one of the most useful indicators to directly quantify the degree of climate warming in high-altitude mountainous areas where meteorological observations are sparse. Using the daily Moderate Resolution Imaging Spectroradiometer (MODIS) LST product (MOD11A1 V6) after eliminating pixels that might be contaminated by clouds, this paper analyzes temporal and spatial variations in the mean LST on the Purog Kangri ice field, Qinghai–Tibetan Plateau, in winter from 2001 to 2018. There was a large increasing trend in LST (0.116 ± 0.05 °C·a−1) on the Purog Kangri ice field during December, while there was no evident LST rising trend in January and February. In December, both the significantly decreased albedo (−0.002 a−1, based on the MOD10A1 V6 albedo product) on the ice field surface and the significantly increased number of clear days (0.322 d·a−1) may be the main reason for the significant warming trend in the ice field. In addition, although the two highest LST of December were observed in 2017 and 2018, a longer data set is needed to determine whether this is an anomaly or a hint of a warmer phase of the Purog Kangri ice field in December.

scholarly journals The Impact of Seasonality and Land Cover on the Consistency of Relationship between Air Temperature and LST Derived from Landsat 7 and MODIS at a Local Scale: A Case Study in Southern Ontario

Land ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 672
Author(s):  
Michael Burnett ◽  
Dongmei Chen
Keyword(s):  
Land Cover ◽  
Spatial Resolution ◽  
Air Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Southern Ontario ◽  
Landsat 7 ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Impact

Land surface temperature (LST) and air temperature (Tair) have been commonly used to analyze urban heat island (UHI) effects throughout the world, with noted variations based on vegetation distribution. This research has compared time series LST data acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) platforms, Landsat 7 Enhanced Thematic Mapper (ETM+) and Tair from weather stations in the Southern Ontario area. The influence of the spatial resolution, land cover, vegetated surfaces, and seasonality on the relationship between LST and in situ Tair were examined. The objective is to identify spatial and seasonal differences amongst these different spatial resolution LST products and Tair, along with the causes for variations at a localized scale. Results show that MODIS LST from Terra had stronger relationships with Landsat 7 LST than those from Aqua. Tair demonstrated weaker correlations with Landsat LST than with MODIS LST in sparsely vegetated and urban areas during the summer. Due to the winter’s ability to smooth heterogenous surfaces, both LST and Tair showed stronger relationships in winter than summer over every land cover, except with coarse spatial resolutions on forested surfaces.

scholarly journals Precipitation Deficit Flash Droughts over the United States

2016 ◽  
Vol 17 (4) ◽  
pp. 1169-1184 ◽  
Author(s):  
Kingtse C. Mo ◽  
Dennis P. Lettenmaier
Keyword(s):  
United States ◽  
Pacific Northwest ◽  
Heat Wave ◽  
Great Plains ◽  
Land Surface ◽  
The United States ◽  
Southern Great Plains ◽  
Physical Mechanisms ◽  
The Pacific ◽  
Surface Models

Abstract Flash drought refers to relatively short periods of warm surface temperature and anomalously low and rapid decreasing soil moisture (SM). Based on the physical mechanisms associated with flash droughts, these events are classified into two categories: heat wave and precipitation P deficit flash droughts. In previous work, the authors have defined heat wave flash droughts as resulting from the confluence of severe warm air temperature Tair, which increases evapotranspiration (ET), and anomalously low and decreasing SM. Here, a second type of flash drought caused by precipitation deficits is explored. The authors term these events P-deficit flash droughts, which they associate with lack of P. Precipitation deficits cause ET to decrease and temperature to increase. The P-deficit flash droughts are analyzed based on observations of P, Tair, and SM and ET reconstructed using land surface models for the period 1916–2013. The authors find that P-deficit flash droughts are more common than heat wave flash droughts. They are about twice as likely to occur as heat wave flash droughts over the conterminous United States. They are most prevalent over the southern United States with maxima over the southern Great Plains and the Southwest, in contrast to heat wave flash droughts that are mostly likely to occur over the Midwest and the Pacific Northwest, where the vegetation cover is dense.

scholarly journals Remote Sensing of Atmospheric Water Vapor Using the Moderate Resolution Imaging Spectroradiometer

2005 ◽  
Vol 22 (3) ◽  
pp. 309-314 ◽  
Author(s):  
P. Albert ◽  
R. Bennartz ◽  
R. Preusker ◽  
R. Leinweber ◽  
J. Fischer
Keyword(s):  
Water Vapor ◽  
Great Plains ◽  
Atmospheric Water Vapor ◽  
Atmospheric Water ◽  
Southern Great Plains ◽  
Moderate Resolution ◽  
Atmospheric Radiation Measurement ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Land Surfaces

Abstract This paper presents first validation results for an algorithm developed for the retrieval of integrated columnar water vapor from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board the polar-orbiting Terra and Aqua platforms. The algorithm is based on the absorption of reflected solar radiation by atmospheric water vapor and allows the retrieval of integrated water vapor above cloud-free land surfaces. A comparison of the retrieved water vapor with measurements of the Microwave Water Radiometer at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for a 10-month period in 2002 showed an rms deviation of 1.7 kg m−2 and a bias of 0.6 kg m−2. A comparison with radio soundings in central Europe from July 2002 to April 2003 showed an rms deviation of 2 kg m−2 and a bias of −0.8 kg m−2.

scholarly journals Summertime Continental Shallow Cumulus Cloud Detection Using GOES-16 Satellite and Ground-Based Stereo Cameras at the DOE ARM Southern Great Plains Site

2021 ◽  
Vol 13 (12) ◽  
pp. 2309
Author(s):  
Jingjing Tian ◽  
Yunyan Zhang ◽  
Stephen A. Klein ◽  
Likun Wang ◽  
Rusen Öktem ◽  
...  
Keyword(s):  
Great Plains ◽  
Land Surface ◽  
Detection Threshold ◽  
Department Of Energy ◽  
Surface Reflectance ◽  
Cloud Detection ◽  
Southern Great Plains ◽  
Clear Sky ◽  
Shallow Cumulus ◽  
Stereo Cameras

Summertime continental shallow cumulus clouds (ShCu) are detected using Geostationary Operational Environmental Satellite (GOES)-16 reflectance data, with cross-validation by observations from ground-based stereo cameras at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. A ShCu cloudy pixel is identified when the GOES reflectance exceeds the clear-sky surface reflectance by a reflectance detection threshold of ShCu, ΔR. We firstly construct diurnally varying clear-sky surface reflectance maps and then estimate the ∆R. A GOES simulator is designed, projecting the clouds reconstructed by stereo cameras towards the surface along the satellite’s slanted viewing direction. The dynamic ShCu detection threshold ΔR is determined by making the GOES cloud fraction (CF) equal to the CF from the GOES simulator. Although there are temporal variabilities in ΔR, cloud fractions and cloud size distributions can be well reproduced using a constant ΔR value of 0.045. The method presented in this study enables daytime ShCu detection, which is usually falsely reported as clear sky in the GOES-16 cloud mask data product. Using this method, a new ShCu dataset can be generated to bridge the observational gap in detecting ShCu, which may transition into deep precipitating clouds, and to facilitate further studies on ShCu development over heterogenous land surface.

Challenges of Brush Management Treatment Effectiveness in Southern Great Plains, United States

2021 ◽  
Vol 77 ◽  
pp. 57-65
Author(s):  
Rheinhardt Scholtz ◽  
Samuel D. Fuhlendorf ◽  
Daniel R. Uden ◽  
Brady W. Allred ◽  
Matthew O. Jones ◽  
...  
Keyword(s):  
United States ◽  
Great Plains ◽  
Treatment Effectiveness ◽  
Southern Great Plains ◽  
Brush Management

Characteristics and Predictability of Midwestern United States Drought

2021 ◽  
Author(s):  
Andrew Hoell ◽  
Trent W. Ford ◽  
Molly Woloszyn ◽  
Jason A. Otkin ◽  
Jon Eischeid
Keyword(s):  
United States ◽  
Great Plains ◽  
Land Surface ◽  
Clustering Algorithm ◽  
Snow Water Equivalent ◽  
Southern Oscillation ◽  
Northern Great Plains ◽  
Ohio Valley ◽  
Midwestern United States ◽  
Wave Trains

AbstractCharacteristics and predictability of drought in the Midwestern United States, spanning the Great Plains to the Ohio Valley, at local and regional scales are examined during 1916-2015. Given vast differences in hydroclimatic variability across the Midwest, drought is evaluated in four regions identified using a hierarchical clustering algorithm applied to an integrated drought index based on soil moisture, snow water equivalent, and three-month runoff from land surface models forced by observed analyses. Highlighting the regions containing the Ohio Valley (OV) and Northern Great Plains (NGP), the OV demonstrates a preference for sub-annual droughts, the timing of which can lead to prevalent dry epochs, while the NGP demonstrates a preference for annual-to-multi-annual droughts. Regional drought variations are closely related to precipitation, resulting in a higher likelihood of drought onset or demise during wet seasons: March-November in the NGP and all year in the OV, with a preference for March-May and September-November. Due to the distinct dry season in the NGP, there is a higher likelihood of longer drought persistence, as the NGP is four times more likely to experience drought lasting at least one year compared to the OV. While drought variability in all regions and seasons are related to atmospheric wave trains spanning the Pacific-North American sector, longer-lead predictability is limited to the OV in December-February because it is the only region/season related to slow-varying sea surface temperatures consistent with El Niño-Southern Oscillation. The wave trains in all other regions appear to be generated in the atmosphere, highlighting the importance of internal atmospheric variability in shaping Midwestern drought.

scholarly journals A Slight Temperature Warming Trend Occurred over Lake Ontario from 2001 to 2018

Land ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1315
Author(s):  
Xiaoying Ouyang ◽  
Dongmei Chen ◽  
Shugui Zhou ◽  
Rui Zhang ◽  
Jinxin Yang ◽  
...  
Keyword(s):  
Land Surface ◽  
Lake Ontario ◽  
Kendall Test ◽  
Warming Trend ◽  
Linear Regression Method ◽  
Ground Measurement ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Mean Square Difference

Satellite-derived lake surface water temperature (LSWT) measurements can be used for monitoring purposes. However, analyses based on the LSWT of Lake Ontario and the surrounding land surface temperature (LST) are scarce in the current literature. First, we provide an evaluation of the commonly used Moderate Resolution Imaging Spectroradiometer (MODIS)-derived LSWT/LST (MOD11A1 and MYD11A1) using in situ measurements near the area of where Lake Ontario, the St. Lawrence River and the Rideau Canal meet. The MODIS datasets agreed well with ground sites measurements from 2015–2017, with an R2 consistently over 0.90. Among the different ground measurement sites, the best results were achieved for Hill Island, with a correlation of 0.99 and centered root mean square difference (RMSD) of 0.73 K for Aqua/MYD nighttime. The validated MODIS datasets were used to analyze the temperature trend over the study area from 2001 to 2018, through a linear regression method with a Mann–Kendall test. A slight warming trend was found, with 95% confidence over the ground sites from 2003 to 2012 for the MYD11A1-Night datasets. The warming trend for the whole region, including both the lake and the land, was about 0.17 K year−1 for the MYD11A1 datasets during 2003–2012, whereas it was about 0.06 K year−1 during 2003–2018. There was also a spatial pattern of warming, but the trend for the lake region was not obviously different from that of the land region. For the monthly trends, the warming trends for September and October from 2013 to 2018 are much more apparent than those of other months.

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