Impact of Small-Scale Rainfall Variability on Larger-Scale Spatial Organization of Land–Atmosphere Fluxes

Nykanen, Deborah K.; Foufoula‐Georgiou, Efi; Lapenta, William M.

doi:10.1175/1525-7541(2001)002<0105:iossrv>2.0.co;2

Cited by 31 publications

(20 citation statements)

References 34 publications

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“…Discrepancies in scale also arise when remote sensing estimates are compared to point measurements for validation. Studies have documented the importance of small-scale rainfall variability on runoff simulation (Ogden andJulien 1993, 1994;Winchell et al 1998), radiative transfer computations (Harris et al 2003), estimation of land-atmosphere fluxes (Nykanen et al 2001), and water balance in land surface schemes (Lammering and Dwyer 2000). The impact of ignoring the small-scale rainfall variability and the propagation of this variability via the nonlinear equations of hydrological models can result in significant biases of the predicted variables.…”

Section: Results Obtained With Trmm-pr Observationsmentioning

confidence: 99%

Submesoscale Spatiotemporal Variability of North American Monsoon Rainfall over Complex Terrain

et al. 2007

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The authors analyze information from rain gauges, geostationary infrared satellites, and low earth orbiting radar in order to describe and characterize the submesoscale (Ͻ75 km) spatial pattern and temporal dynamics of rainfall in a 50 km ϫ 75 km study area located in Sonora, Mexico, in the periphery of the North American monsoon system core region. The temporal domain spans from 1 July to 31 August 2004, corresponding to one monsoon season. Results reveal that rainfall in the study region is characterized by high spatial and temporal variability, strong diurnal cycles in both frequency and intensity with maxima in the evening hours, and multiscaling behavior in both temporal and spatial fields. The scaling parameters of the spatial rainfall fields exhibit dependence on the rainfall rate at the synoptic scale. The rainfall intensity exhibits a slightly stronger diurnal cycle compared to the rainfall frequency, and the maximum lag time between the two diurnal peaks is within 2.4 h, with earlier peaks observed for rainfall intensity. The time of maximum cold cloud occurrence does not vary with the infrared threshold temperature used (215-235 K), while the amplitude of the diurnal cycle varies in such a way that deep convective cells have stronger diurnal cycles. Furthermore, the results indicate that the diurnal cycle of cold cloud occurrence can be used as a surrogate for some basic features of the diurnal cycle of rainfall. The spatial pattern and temporal dynamics of rainfall are modulated by topographic features and large-scale features (circulation and moisture fields as related to geographical location). As compared to valley areas, mountainous areas are characterized by an earlier diurnal peak, an earlier date of maximum precipitation, closely clustered rainy hours, frequent yet small rainfall events, and less dependence of precipitation accumulation on elevation. As compared to the northern section of the study area, the southern section is characterized by strong convective systems that peak late diurnally. The results of this study are important for understanding the physical processes involved, improving the representation of submesoscale variability in models, downscaling rainfall data from coarse meteorological models to smaller hydrological scales, and interpreting and validating remote sensing rainfall estimates.

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Section: Results Obtained With Trmm-pr Observationsmentioning

confidence: 99%

Submesoscale Spatiotemporal Variability of North American Monsoon Rainfall over Complex Terrain

et al. 2007

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“…Accurate measurement of precipitation at fine space and time scales has been shown to improve our ability to simulate land surface hydrological processes and states, such as floods and droughts (Ogden andJulien 1993, 1994;Faures et al 1995;Nykanen et al 2001). In particular, previous results suggest that precipitation sampled at 3-h intervals or shorter significantly reduces uncertainties associated with flood prediction (Hossain and Anagnostou 2004;Nijssen and Lettenmaier 2004).…”

Section: Introductionmentioning

confidence: 99%

Multitemporal Analysis of TRMM-Based Satellite Precipitation Products for Land Data Assimilation Applications

Tian

Peters‐Lidard

Choudhury

et al. 2007

Journal of Hydrometeorology

273

164

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In this study, the recent work of Gottschalck et al. and Ebert et al. is extended by assessing the suitability of two Tropical Rainfall Measuring Mission (TRMM)-based precipitation products for hydrological land data assimilation applications. The two products are NASA's gauge-corrected TRMM 3B42 Version 6 (3B42), and the satellite-only NOAA Climate Prediction Center (CPC) morphing technique (CMORPH). The two products were evaluated against ground-based rain gauge-only and gauge-corrected Doppler radar measurements. The analyses were performed at multiple time scales, ranging from annual to diurnal, for the period March 2003 through February 2006. The analyses show that at annual or seasonal time scales, TRMM 3B42 has much lower biases and RMS errors than CMORPH. CMORPH shows season-dependent biases, with overestimation in summer and underestimation in winter. This leads to 50% higher RMS errors in CMORPH's area-averaged daily precipitation than TRMM 3B42. At shorter time scales (5 days or less), CMORPH has slightly less uncertainty, and about 10%-20% higher probability of detection of rain events than TRMM 3B42. In addition, the satellite estimates detect more high-intensity events, causing a remarkable shift in precipitation spectrum. Summertime diurnal cycles in the United States are well captured by both products, although the 8-km CMORPH seems to capture more diurnal features than the 0.25°C MORPH or 3B42 products. CMORPH tends to overestimate the amplitude of the diurnal cycles, particularly in the central United States. Possible causes for the discrepancies between these products are discussed.

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“…Over the US, the highest resolution routinely available precipitation and radiation products have 4 km spatial resolution and an hourly temporal resolution ( [28,29]). Therefore, an active area of current LIS research is to improve upon our precipitation and radiation downscaling using a combination of topographic (e.g., [30]) and statistical/dynamical (e.g., [31]) approaches. Other meteorological inputs such as near-surface air temperature, humidity, pressure, winds and downward longwave radiation are obtained by topographically downscaling atmospheric analyses from NASA and/or NOAA using lapse-rate and hypsometric adjustments to the 1 km GTOPO30 elevation data in LIS as discussed by [27].…”

Section: Lis Coupled and Uncoupled Running Modesmentioning

confidence: 99%

High-performance Earth system modeling with NASA/GSFC’s Land Information System

Peters‐Lidard¹,

Houser

Tian

et al. 2007

Innovations Syst Softw Eng

199

120

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The Land Information System software (LIS; http://lis.gsfc.nasa.gov /, 2006) has been developed to support high-performance land surface modeling and data assimilation. LIS integrates parallel and distributed computing technologies with modern land surface modeling capabilities, and establishes a framework for easy interchange of subcomponents, such as land surface physics, input/output conventions, and data assimilation routines. The software includes multiple land surface models that can be run as a multi-model ensemble on global or regional domains with horizontal resolutions ranging from 2.5 • to 1 km. The software may execute serially or in parallel on various highperformance computing platforms. In addition, the software has well-defined, standard-conforming interfaces and data structures to interface and interoperate with other Earth system models. Developed with the support of an Earth science technology office (ESTO) computational technologies project round 3 cooperative agreement, LIS has helped advance NASA's Earth-Sun division's software engineering principles and practices, while promoting portability, interoperability, and scalability for Earth system modeling. LIS was selected as a co-winner of NASA's 2005 software of the year award.

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Impact of Small-Scale Rainfall Variability on Larger-Scale Spatial Organization of Land–Atmosphere Fluxes

Cited by 31 publications

References 34 publications

Submesoscale Spatiotemporal Variability of North American Monsoon Rainfall over Complex Terrain

Submesoscale Spatiotemporal Variability of North American Monsoon Rainfall over Complex Terrain

Multitemporal Analysis of TRMM-Based Satellite Precipitation Products for Land Data Assimilation Applications

High-performance Earth system modeling with NASA/GSFC’s Land Information System

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