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Xia Y.,National Centers for Environmental Prediction Environmental Modeling Center | Xia Y.,I M Systems Group | Ford T.W.,Texas A&M University | Wu Y.,National Centers for Environmental Prediction Environmental Modeling Center | And 3 more authors.
Journal of Applied Meteorology and Climatology | Year: 2015

The North American Soil Moisture Database (NASMD) was initiated in 2011 to provide support for developing climate forecasting tools, calibrating land surface models, and validating satellite-derived soil moisture algorithms. The NASMD has collected data from over 30 soil moisture observation networks providing millions of in situ soil moisture observations in all 50 states, as well as Canada and Mexico. It is recognized that the quality of measured soil moisture in NASMD is highly variable because of the diversity of climatological conditions, land cover, soil texture, and topographies of the stations, and differences in measurement devices (e.g., sensors) and installation. It is also recognized that error, inaccuracy, and imprecision in the data can have significant impacts on practical operations and scientific studies. Therefore, developing an appropriate quality control procedure is essential to ensure that the data are of the best quality. In this study, an automated quality control approach is developed using the North American Land Data Assimilation System, phase 2 (NLDAS-2), Noah soil porosity, soil temperature, and fraction of liquid and total soil moisture to flag erroneous and/or spurious measurements. Overall results show that this approach is able to flag unreasonable values when the soil is partially frozen. A validation example using NLDAS-2 multiple model soil moisture products at the 20-cm soil layer showed that the quality control procedure had a significant positive impact in Alabama, North Carolina, and west Texas. It had a greater impact in colder regions, particularly during spring and autumn. Over 433 NASMD stations have been quality controlled using the methodology proposed in this study, and the algorithm will be implemented to control data quality from the other ~1200 NASMD stations in the near future. © 2015 American Meteorological Society.


Reeves H.D.,University of Oklahoma | Elmore K.L.,University of Oklahoma | Manikin G.S.,National Centers for Environmental Prediction Environmental Modeling Center | Stensrud D.J.,National Severe Storms Laboratory
Weather and Forecasting | Year: 2011

North American Mesoscale Model (NAM) forecasts of low-level temperature and dewpoint during persistent valley cold pools in the Bonneville Basin of Utah are assessed. Stations near the east sidewall have a daytime cold and nighttime warm bias. This is due to a poor representation of the steep slopes on this side of the basin. Basin stations where the terrain is better represented by the model have a distinct warm, moist bias at night. Stations in snow-covered areas have a cold bias for both day and night. Biases are not dependent on forecast lead or validation time. Several potential causes for the various errors are considered in a series of sensitivity experiments. An experiment with 4-km grid spacing, which better resolves the gradient of the slopes on the east side of the basin, yields smaller errors along the east corridor of the basin. The NAM assumes all soil water freezes at a temperature of 273 K. This is likely not representative of the freezing temperature in the salt flats in the western part of the basin, since salt reduces the freezing point of water. An experiment testing this hypothesis shows that reducing the freezing point of soil water in the salt flats leads to an average error reduction between 1.5 and 4 K, depending on the station and time of day. Using a planetary boundary layer scheme that has greater mixing alleviates the cold bias over snow somewhat, but the exact source of this bias could not be determined. © 2011 American Meteorological Society.


Xia Y.,National Centers for Environmental Prediction Environmental Modeling Center | Xia Y.,EMC | Ek M.B.,National Centers for Environmental Prediction Environmental Modeling Center | Wu Y.,National Centers for Environmental Prediction Environmental Modeling Center | And 3 more authors.
Journal of Hydrometeorology | Year: 2015

Soil moisture observations from seven observational networks (spanning portions of seven states) with different biome and climate conditions were used in this study to evaluate multimodel simulated soil moisture products. The four land surface models, including Noah, Mosaic, Sacramento soil moisture accounting (SAC), and the Variable Infiltration Capacity model (VIC), were run within phase 2 of the North American Land Data Assimilation System (NLDAS-2), with a 1/8° spatial resolution and hourly temporal resolution. Hundreds of sites in Alabama, Colorado, Michigan, Nebraska, Oklahoma, West Texas, and Utah were used to evaluate simulated soil moisture in the 0-10-, 10-40-, and 40-100-cm soil layers. Soil moisture was spatially averaged in each state to reduce noise. In general, the four models captured broad features (e.g., seasonal variation) of soil moisture variations in all three soil layers in seven states, except for the 10-40-cm soil layer in West Texas and the 40-100-cm soil layer in Alabama, where the anomaly correlations are weak. Overall, Mosaic, SAC, and the ensemble mean have the highest simulation skill and VIC has the lowest simulation skill. The results show that Noah and VIC are wetter than the observations while Mosaic and SAC are drier than the observations, mostly likely because of systematic errors in model evapotranspiration. © 2015 American Meteorological Society.


Wolff J.K.,U.S. National Center for Atmospheric Research | Ferrier B.S.,National Centers for Environmental Prediction Environmental Modeling Center | Mass C.F.,University of Washington
Bulletin of the American Meteorological Society | Year: 2012

The numerical weather prediction (NWP) workshop on model physics with an emphasis on short-range prediction, July 26-28, 2011, Maryland, identified near-term opportunities for making urgently needed physics improvements in the models. The workshop also established a longer-term framework for closer collaboration between research and operations in the development of forecast model physics. Topics discussed include representation of physics processes in NWP models, including atmospheric radiation, land surface modeling, and cloud microphysical processes. The workshop participants recommended the some action items such as EMC to establish a science advisory board and EMC and the DTC to work closely to promote R&O collaboration through working group meetings and workshops. The members also highlighted that NOAA/NWS should acquire increased computing resources for developing the next-generation high-resolution deterministic and ensemble modeling systems.


Carlis D.L.,Howard University | Carlis D.L.,National Weather Service - NWS | Carlis D.L.,National Centers for Environmental Prediction Environmental Modeling Center | Chen Y.-L.,University of Hawaii at Manoa | Morris V.R.,Howard University
Monthly Weather Review | Year: 2010

The fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5) coupled with the Noah land surface model (LSM) is employed to simulate island-scale airflow and circulations over Maui County, Hawaii, under summer trade wind conditions, during July-August 2005. The model forecasts are validated by surface observations with good agreement. In this study, it is shown that a previously known closed circulation over the Central Valley of Maui, or the Maui vortex, represents the northern cyclonic vortex of the dual-counter-rotating vortices in the lee of Haleakala, which extend up to the base of the trade wind inversion with a westerly reversed flow (>2 m s -1). At low levels, the northern cyclonic vortex is more pronounced than the southern anticyclonic vortex. The asymmetric structure of the dual vortices is related to the shape of Haleakala and the flow deflection by the West Maui Mountains. The Maui vortex has a relatively narrow east-west extent in the lowest levels, especially at night, due to the deflected strong northerly/northeasterly winds from the windward foothills of the West Maui Mountains. Unlike the lee vortices off the leeside coast of the island of Hawaii, the Maui vortex and the westerly return flow in low levels are mainly over land and are strongly modulated by the diurnal heating cycle. In addition, the location and horizontal and vertical extent are affected by the trade wind speed and latent heat release. Over the West Maui Mountains, with their height below the trade wind inversion, dual-counter-rotating vortices are present below the 1-km level in the wake, with strong downslope flow on the leeside slopes followed by a hydraulic jump. In the afternoon, downslope winds are weak, with combined westerly return/sea-breeze flow along the leeside coast. Orographic blocking is also evident over eastern Molokai with strong downslope winds, especially at night. © 2010 American Meteorological Society.


Han J.,Wyle | Pan H.-L.,National Centers for Environmental Prediction Environmental Modeling Center
Weather and Forecasting | Year: 2011

A new physics package containing revised convection and planetary boundary layer (PBL) schemes in the National Centers for Environmental Prediction's Global Forecast System is described. The shallow convection (SC) scheme in the revision employs a mass flux parameterization replacing the old turbulent diffusion-based approach. For deep convection, the scheme is revised to make cumulus convection stronger and deeper to deplete more instability in the atmospheric column and result in the suppression of the excessive grid-scale precipitation. The PBL model was revised to enhance turbulence diffusion in stratocumulus regions. A remarkable difference between the new and old SC schemes is seen in the heating or cooling behavior in lower-atmospheric layers above the PBL. While the old SC scheme using the diffusion approach produces a pair of layers in the lower atmosphere with cooling above and heating below, the new SC scheme using the mass-flux approach produces heating throughout the convection layers. In particular, the new SC scheme does not destroy stratocumulus clouds off the west coasts of South America and Africa as the old scheme does. On the other hand, the revised deep convection scheme, having a larger cloud-base mass flux and higher cloud tops, appears to effectively eliminate the remaining instability in the atmospheric column that is responsible for the excessive grid-scale precipitation in the old scheme. The revised PBL scheme, having an enhanced turbulence mixing in stratocumulus regions, helps prevent too much low cloud from forming. An overall improvement was found in the forecasts of the global 500-hPa height, vector wind, and continental U.S. precipitation with the revised model. Consistent with the improvement in vector wind forecast errors, hurricane track forecasts are also improved with the revised model for both Atlantic and eastern Pacific hurricanes in 2008. © 2011 American Meteorological Society.


Xia Y.,National Centers for Environmental Prediction Environmental Modeling Center | Xia Y.,EMC | Ek M.B.,National Centers for Environmental Prediction Environmental Modeling Center | Wu Y.,National Centers for Environmental Prediction Environmental Modeling Center | And 3 more authors.
Journal of Hydrometeorology | Year: 2015

In this second part of a two-part paper, the impacts of soil texture and vegetation type misclassification and their combined effect on soilmoisture, evapotranspiration, and total runoff simulation are investigated using the Noah model. The results show that these impacts are significant for most regions and soil layers, although they vary depending on soil texture classification, vegetation type, and season. The use of site-observed soil texture classification and vegetation type in the model does not necessarily improve anomaly correlations and reduce mean absolute error for soil moisture simulations. Instead, results are mixed when examining all regions and soil layers. This is attributed to the compensation effects (e.g., effect of ill-calibrated model parameters), as Noah has been more or less calibrated with model-specified soil texture classification and vegetation type. The site-based analysis shows that Noah can reasonably simulate the variation of daily evapotranspiration, soil moisture, and total runoff when soil texture classification (vegetation type) is corrected from loam (forest) to clay (grasslands) or vice versa. This suggests that the performance of Noah can be further improved by tuning model parameters when site-observed soil texture and vegetation type are used. © 2015 American Meteorological Society.

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