Modeling and Satellite Remote Sensing of the Meteorological Impacts of Irrigation During the 2012 Central Plains Drought

As irrigation is increasingly needed for agricultural production, it is becoming progressively more important to understand not only how irrigation impacts water availability, but how the introduction of this water into the soil impacts weather and climate through land-atmosphere interactions. In the summer of 2012, the Central Plains of the United States experienced one of its most severe droughts on record. This study examines the meteorological impacts of irrigation during this drought through observations and model simulations using the Community Land Model (CLM) coupled to the Weather Research and Forecasting (WRF) model. A simple parameterization of irrigation processes is added into the WRF model. In addition to keeping soil moisture in irrigated areas at a minimum of 50% of soil moisture capacity, this irrigation scheme also has the following new features: (1) accurate representation of the spatial distribution of irrigation area in the study domain by using MODIS-based 250-m resolution land surface classification; and (2) improved representation of the time series of leaf area index (LAI) values derived from crop modeling and satellite observations in both irrigated and non-irrigated areas. Several numerical sensitivity experiments are conducted. The WRF-simulated temperature field when including soil moisture and LAI modification within the model is shown to be most consistent with ground and satellite observations, all indicating a 2-3 K decrease of temperature in irrigated areas compared to the control run. Modification of leaf area index in irrigated and dryland areas led to smaller changes, with a 0.2 K temperature decrease in irrigated areas and up to a 0.5 K temperature increase in dryland areas. Furthermore, the increased soil moisture and modified leaf area index is shown to lead to increases in surface divergence, increases in surface pressure, and decreases in planetary boundary layer height over irrigated areas. Advisor: Jun Wan

Modeling and Satellite Remote Sensing of the Meteorological Impacts of Irrigation During the 2012 Central Plains Drought

As irrigation is increasingly needed for agricultural production, it is becoming progressively more important to understand not only how irrigation impacts water availability, but how the introduction of this water into the soil impacts weather and climate through land-atmosphere interactions. In the summer of 2012, the Central Plains of the United States experienced one of its most severe droughts on record. This study examines the meteorological impacts of irrigation during this drought through observations and model simulations using the Community Land Model (CLM) coupled to the Weather Research and Forecasting (WRF) model. A simple parameterization of irrigation processes is added into the WRF model. In addition to keeping soil moisture in irrigated areas at a minimum of 50% of soil moisture capacity, this irrigation scheme also has the following new features: (1) accurate representation of the spatial distribution of irrigation area in the study domain by using MODIS-based 250-m resolution land surface classification; and (2) improved representation of the time series of leaf area index (LAI) values derived from crop modeling and satellite observations in both irrigated and non-irrigated areas. Several numerical sensitivity experiments are conducted. The WRF-simulated temperature field when including soil moisture and LAI modification within the model is shown to be most consistent with ground and satellite observations, all indicating a 2-3 K decrease of temperature in irrigated areas compared to the control run. Modification of leaf area index in irrigated and dryland areas led to smaller changes, with a 0.2 K temperature decrease in irrigated areas and up to a 0.5 K temperature increase in dryland areas. Furthermore, the increased soil moisture and modified leaf area index is shown to lead to increases in surface divergence, increases in surface pressure, and decreases in planetary boundary layer height over irrigated areas. Advisor: Jun Wan

Mesoscale Modeling of the Meteorological Impacts of Irrigation during the 2012 Central Plains Drought

In the summer of 2012, the central plains of the United States experienced one of its most severe droughts on record. This study examines the meteorological impacts of irrigation during this drought through observations and model simulations using the Community Land Model coupled to the Weather Research and Forecasting (WRF) Model. A simple parameterization of irrigation processes is added into the WRF Model. In addition to keeping soil moisture in irrigated areas at a minimum of 50% of soil moisture hold capacity, this irrigation scheme has the following new features: 1) accurate representation of the spatial distribution of irrigation area in the study domain by using a MODIS-based land surface classification with 250-m pixel size and 2) improved representation of the time series of leaf area index (LAI) values derived from crop modeling and satellite observations in both irrigated and nonirrigated areas. Several numerical sensitivity experiments are conducted. The WRF-simulated temperature field when including soil moisture and LAI modification within the model is shown to be most consistent with ground and satellite observations, all indicating a temperature decrease of 2–3K in irrigated areas relative to the control run. Modification of LAI in irrigated and dryland areas led to smaller changes, with a 0.2-K temperature decrease in irrigated areas and up to a 0.5-K temperature increase in dryland areas. Furthermore, the increased soil moisture and modified LAI are shown to lead to statistically significant increases in surface divergence and surface pressure and to decreases in planetary boundary layer height over irrigated areas

Mesoscale Modeling of the Meteorological Impacts of Irrigation during the 2012 Central Plains Drought

In the summer of 2012, the central plains of the United States experienced one of its most severe droughts on record. This study examines the meteorological impacts of irrigation during this drought through observations and model simulations using the Community Land Model coupled to the Weather Research and Forecasting (WRF) Model. A simple parameterization of irrigation processes is added into the WRF Model. In addition to keeping soil moisture in irrigated areas at a minimum of 50% of soil moisture hold capacity, this irrigation scheme has the following new features: 1) accurate representation of the spatial distribution of irrigation area in the study domain by using a MODIS-based land surface classification with 250-m pixel size and 2) improved representation of the time series of leaf area index (LAI) values derived from crop modeling and satellite observations in both irrigated and nonirrigated areas. Several numerical sensitivity experiments are conducted. The WRF-simulated temperature field when including soil moisture and LAI modification within the model is shown to be most consistent with ground and satellite observations, all indicating a temperature decrease of 2–3K in irrigated areas relative to the control run. Modification of LAI in irrigated and dryland areas led to smaller changes, with a 0.2-K temperature decrease in irrigated areas and up to a 0.5-K temperature increase in dryland areas. Furthermore, the increased soil moisture and modified LAI are shown to lead to statistically significant increases in surface divergence and surface pressure and to decreases in planetary boundary layer height over irrigated areas

A Multi-sensor View of the 2012 Central Plains Drought from Space

In summer of 2012, the Central Plains of the United States experienced its most severe drought since the ground-based data record began in the late 1900s. By using comprehensive satellite data from MODIS (Moderate Resolution Imaging Spectroradiometer) and TRMM (Tropical Rainfall Measuring Mission), along with in-situ observations, this study documents the geophysical parameters associated with this drought, and thereby providing, for the first time, a large-scale observation-based view of the extent to which the land surface temperature and vegetation can likely be affected by both the severe drought and the agricultural response (irrigation) to the drought. Over non-irrigated area, 2012 summer daytime land surface temperature (LSl) , and Normalized Difference Vegetation Index (NDVI) monthly anomalies (with respect to climate in 2002-2011) are often respectively greater than 5 K and negative, with some extreme values of 10K and -0.2 (Le., no green vegetation). In contrast, much smaller anomalies \u3c 2 K) of LST and nearly the same NDVI are found over irrigated areas. Precipitation received was an average of 5.2 cm less, while both fire counts and fire radiative power were doubled, thus contributing in part to a nearly 100% increase of aerosol optical depth in many forested areas (close to intermountain west). Water vapor amount, while decreased over the southern part, indeed slightly increased in the northern part of Central Plains. As expected, cloud fraction anomaly is negative in the entire Central Plains; however, the greatest reduction of cloud fraction is found over the irrigated areas, which is in contrast to past modeling studies showing that more irrigation, because of its impact on LST, may lead to increase of cloud fraction

Potential application of VIIRS Day/Night Band for monitoring nighttime surface PM\u3csub\u3e2.5\u3c/sub\u3e air quality from space

A pilot study is conducted to illustrate the potential of using radiance data collected by the Day/Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polarorbiting Partnership (S-NPP) satellite for particulate matter (PM) air quality monitoring at night. The study focuses on the moonless and cloudless nights in Atlanta, Georgia during August-October 2012.We show with radiative transfer calculations that DNB at night is sensitive to the change of aerosols and much less sensitive to the change of water vapor in the atmosphere illuminated by common outdoor light bulbs at the surface. We further show both qualitatively that the contrast of DNB images can indicate the change of air quality at the urban scale, and quantitatively that change of light intensity during the night (as characterized by VIIRS DNB) reflects the change of surface PM2.5. Compared to four meteorological variables (u and v components of surface wind speed, surface pressure, and columnar water vapor amount) that can be obtained from surface measurements, the DNB light intensity is the only variable that shows either the largest or second largest correlation with surface PM2.5 measured at 5 different sites. A simple multivariate regression model with consideration of the change of DNB light intensity can yield improved estimate of surface PM2.5 as compared to the model with consideration of meteorological variables only. Cross validation of this DNB-based regression model shows that the estimated surface PM2.5 concentration has nearly no bias and a linear correlation coefficient (R) of 0.67 with respect to the corresponding hourly observed surface PM2.5 concentration. Furthermore, groundbased observations support that surface PM2.5 concentration at the VIIRS night overpass (~1:00 am local) time is representative of daily-mean PM2.5 air quality (R = 0.82 and mean bias of -0.1 mg m-3). While the potential appears promising, mapping surface PM2.5 from space with visible light at night still face various challenges and the strategies to address some of these challenges are elaborated for future studies