Craig R. Ferguson

Estimating the water budget of major US river basins via remote sensing

Nine satellite-based products, each of which provides information about land surface water budget terms, are used to estimate seasonal and annual variations in the water budget of the major river basins of the conterminous USA from 2003 to 2006. The remotely sensed terms are compared with gridded gauge precipitation, and estimates of evapotranspiration (E) and total water storage (TWS) derived from the Variable Infiltration Capacity (VIC) macroscale hydrology model. Among the remote sensing estimates, precipitation has the largest uncertainties. In general, apparent errors for E and TWS show substantial spatial variations, but the consistencies among these remote sensing products are greater than among precipitation products, possibly due in part to similarities in methodology, especially for TWS. Inferred run-off (as a residual of remote sensing estimates of precipitation, E, and TWS) is generally overestimated, due both to excessive precipitation and underestimation of combined E and terrestrial water storage change (TWSC) from remote sensing.

Satellite Microwave Remote Sensing of Daily Land Surface Air Temperature Minima and Maxima From AMSR-E

We present an approach to retrieve daily minimum and maximum 2-m height air temperatures from 18.7, and 23.8 GHz H and V polarized brightness temperature from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) during the snow free season. The approach accounts, with minimal ancillary data, for vertically integrated atmospheric water vapor, and variable surface emissivity due to open water and vegetation. Retrieved temperatures were evaluated using Northern Hemisphere weather stations and independent satellite-based air temperatures from the Atmosphere Infrared Sounder and Advanced Microwave Sounding Unit (AIRS/AMSU; hereafter AIRS) sensors on Aqua. The retrieved temperatures are within 1.0 - 3.5 K of surface weather station measurements for vegetated locations, but uncertainty can exceed 4 K for desert and sparsely vegetated regions, mainly due to site to site biases. The AIRS and AMSR-E temperature retrievals generally agree more closely with one another than with weather stations and are generally within 1.0-2.8 K over vegetated regions, but with less agreement ( > 4 K ) over desert and mountainous regions. Additional useful information produced by our approach includes open water fraction, vegetation optical depth and atmospheric water vapor. The results of this study provide inputs for land surface models and a new approach for monitoring of land surface air temperatures with well quantified accuracy and precision.

A Global Intercomparison of Modeled and Observed Land–Atmosphere Coupling*

AbstractLand–atmosphere coupling strength or the degree to which land surface anomalies influence boundary layer development—and in extreme cases, rainfall—is arguably the single most fundamental criterion for evaluating hydrological model performance. The Global Land–Atmosphere Coupling Experiment (GLACE) showed that strength of coupling and its representation can affect a model’s ability to simulate climate predictability at the seasonal time scale. And yet, the lack of sufficient observations of coupling at appropriate temporal and spatial scales has made achieving “true” coupling in models an elusive goal. This study uses Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) soil moisture (SM), multisensor remote sensing (RS) evaporative fraction (EF), and Atmospheric Infrared Sounder (AIRS) lifting condensation level (LCL) to evaluate the realism of coupling in the Global Land Data Assimilation System (GLDAS) suite of land surface models (LSMs), Princeton Global Forcing Variable ...

Quantifying uncertainty in a remote sensing-based estimate of evapotranspiration over continental USA

We calculate evapotranspiration (E) from remote sensing (RS) data using the Penman–Monteith model over continental USA for four years (2003–2006) and explore, through an ensemble generation framework, the impact of input dataset (meteorological, radiation and vegetation) selection on performance (uncertainty) at the monthly time-scale. The impact of failed or missed RS retrievals and algorithmic assumptions are also quantified. To evaluate bias, we inter-compare RS-E with three independent sources of E: Variable Infiltration Capacity (VIC)-model simulated, North American Regional Reanalysis (NARR) inferred, and Gravity Recovery and Climate Experiment (GRACE) inferred. Overall, we find that the choice of vegetation parameterization, followed by surface temperature, has the greatest impact on RS-E uncertainty. Additional uncertainty (4–18%) is linked to sources of net radiation—used to scale instantaneous RS-E under the assumption of constant daytime evaporative fraction—including the Surface Radiation Budget (SRB), International Satellite Cloud Climatology Project (ISCCP), and North American Land Data Assimilation System (NLDAS)-VIC. The ensemble median agrees to within 21% of VIC-modelled E, except for the Colorado and Great Basins for which the need for a soil moisture constraint on RS-E becomes evident.

Observed Land–Atmosphere Coupling from Satellite Remote Sensing and Reanalysis

AbstractThe lack of observational data for use in evaluating the realism of model-based land–atmosphere feedback signal and strength has been deemed a major obstacle to future improvements to seasonal weather prediction by the Global Land–Atmosphere Coupling Experiment (GLACE). To address this need, a 7-yr (2002–09) satellite remote sensing data record is exploited to produce for the first time global maps of predominant coupling signals. Specifically, a previously implemented convective triggering potential (CTP)–humidity index (HI) framework for describing atmospheric controls on soil moisture–rainfall feedbacks is revisited and generalized for global application using CTP and HI from the Atmospheric Infrared Sounder (AIRS), soil moisture from the Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (AMSR-E), and the U.S. Climate Prediction Center (CPC) merged satellite rainfall product (CMORPH). Based on observations taken during an AMSR-E-derived convective rainfall season, the glob...

Temporal Variability of Land-Atmosphere Coupling and Its Implications for Drought over the Southeast United States

AbstractDroughts represent a significant source of social and economic damage in the southeast United States. Having sufficient warning of these extreme events enables managers to prepare for and potentially mitigate the severity of their impacts. A seasonal hydrologic forecast system can provide such warning, but current forecast skill is low during the convective season when precipitation is affected by regionally varying land surface heat flux contributions. Previous studies have classified regions into coupling regimes based on the tendency of surface soil moisture anomalies to trigger convective rainfall. Until now, these classifications have been aimed at assessing the long-term dominant feedback signal. Sufficient focus has not been placed on the temporal variability that underlies this signal. To better understand this aspect of coupling, a new classification methodology suitable at daily time scales is developed. The methodology is based on the joint probability space of surface soil moisture, co...

An Evaluation of Satellite Remote Sensing Data Products for Land Surface Hydrology: Atmospheric Infrared Sounder*

Abstract The skill of instantaneous Atmospheric Infrared Sounder (AIRS) retrieved near-surface meteorology, including surface skin temperature (Ts), air temperature (Ta), specific humidity (q), and relative humidity (RH), as well as model-derived surface pressure (Psurf) and 10-m wind speed (w), is evaluated using collocated National Climatic Data Center (NCDC) in situ observations, offline data from the North American Land Data Assimilation System (NLDAS), and geostationary remote sensing (RS) data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI). Such data are needed for RS-based water cycle monitoring in areas without readily available in situ data. The study is conducted over the continental United States and Africa for a period of more than 6 years (2002–08). For both regions, it provides for the first time the geographic distribution of AIRS retrieval performance. Through conditional sampling, attribution of retrieval errors to scene atmospheric and surface conditions is performed. Th...

Impact of land-atmospheric coupling in CFSv2 on drought prediction

Recent summers in the United States have been plagued by intense droughts that have caused significant damage to crops and have had a large impact on society. The ability to forecasts such events would allow for preparations that could help reduce the impact on society. Coupled land–atmosphere–ocean models were created to provide such forecasts but there are large uncertainties associated with their predictions. The predictive skill of these models is particularly low during the convective season due to the weaker connections with the oceans and an increase in the land–atmosphere interactions. To better understand the degradation of forecasts skill during the summer months and its connection to the land–atmosphere interactions we analyze National Centers for Environmental Prediction’s Climate Forecast System Version 2 (CFSv2) in terms of its climatological land–atmosphere interactions. To do this we use a recently developed classification of land–atmosphere interactions and other diagnostic variables to compare the reanalysis from the Climate Forecast System (CFSR) with CFSv2 re-forecasts (CFSRR) over the period 1982–2009. Coupling in the CFSRR tends toward the wet coupling regime for most areas east of the Rocky Mountains. Although the specific mechanism driving CFSRR to wet coupling state varies by region, the overall cause is enhanced vegetation rooting depth, originally implemented to address a near-surface warm bias in CFSR. The long-term tendency to wet coupling precludes the forecast model from consistently predicting and maintaining drought over the continental US.

Land–Atmosphere Coupling at the Southern Great Plains Atmospheric Radiation Measurement (ARM) Field Site and Its Role in Anomalous Afternoon Peak Precipitation

AbstractThe multimodel Global Land–Atmosphere Coupling Experiment (GLACE) identified the semiarid Southern Great Plains (SGP) as a hotspot for land–atmosphere (LA) coupling and, consequently, land-derived temperature and precipitation predictability. The area including and surrounding the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) SGP Climate Research Facility has in particular been well studied in the context of LA coupling. Observation-based studies suggest a coupling signal that is much weaker than modeled, if not elusive. Using North American Regional Reanalysis and North American Land Data Assimilation System data, this study provides a 36-yr (1979–2014) climatology of coupling for ARM-SGP that 1) unifies prior interdisciplinary efforts and 2) isolates the origin of the (weak) coupling signal. Specifically, the climatology of a prominent convective triggering potential–low-level humidity index (CTP–HIlow) coupling classification is linked to corresponding synoptic–mesoscale wea...

The Diurnal Cycle of Precipitation in Regional Spectral Model Simulations over West Africa: Sensitivities to Resolution and Cumulus Schemes

AbstractAs a basic form of climate patterns, the diurnal cycle of precipitation (DCP) can provide a key test bed for model reliability and development. In this study, the DCP over West Africa was simulated by the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM) during the monsoon season (April–September) of 2005. Three convective parameterization schemes (CPSs), single-layer simplified Arakawa–Schubert (SAS), multilayer relaxed Arakawa–Schubert (RAS), and new Kain–Fritsch (KF2), were evaluated at two horizontal resolutions (20 and 10 km). The Benin mesoscale site was singled out for additional investigation of resolution effects. Harmonic analysis was used to characterize the phase and amplitude of the DCP. Compared to satellite observations, the overall spatial distributions of amplitude were well captured at regional scales. The RSM properly reproduced the observed late afternoon peak over land and the early morning peak over ocean. Nevertheless, the peak time was early...