Evaluation of Surface Sensible Weather Forecasts by the WRF and the Eta Models over the Western United States

2005 ◽  
Vol 20 (5) ◽  
pp. 812-821 ◽  
Author(s):  
William Y. Y. Cheng ◽  
W. James Steenburgh

Abstract An evaluation of the surface sensible weather forecasts using high-density observations provided by the MesoWest cooperative networks illustrates the performance characteristics of the Cooperative Institute for Regional Prediction (CIRP) Weather Research and Forecast (WRF) and the Eta Models over the western United States during the 2003 warm season (June–August). In general, CIRP WRF produced larger 2-m temperature and dewpoint mean absolute and bias errors (MAEs and BEs, respectively) than the Eta. CIRP WRF overpredicted the 10-m wind speed, whereas the Eta exhibited an underprediction with a comparable error magnitude to CIRP WRF. Tests using the Oregon State University (OSU) Land Surface Model (LSM) in CIRP WRF, instead of a simpler slab-soil model, suggest that using a more sophisticated LSM offers no overall advantage in reducing WRF BEs and MAEs for the aforementioned surface variables. Improvements in the initialization of soil temperature in the slab-soil model, however, did reduce the temperature bias in CIRP WRF. These results suggest that improvements in LSM initialization may be as or more important than improvements in LSM physics. A concerted effort must be undertaken to improve both the LSM initialization and parameterization of coupled land surface–boundary layer processes to produce more accurate surface sensible weather forecasts.

2020 ◽  
Vol 21 (10) ◽  
pp. 2343-2357
Author(s):  
Huancui Hu ◽  
L. Ruby Leung ◽  
Zhe Feng

ABSTRACTWarm-season rainfall associated with mesoscale convective systems (MCSs) in the central United States is characterized by higher intensity and nocturnal timing compared to rainfall from non-MCS systems, suggesting their potentially different footprints on the land surface. To differentiate the impacts of MCS and non-MCS rainfall on the surface water balance, a water tracer tool embedded in the Noah land surface model with multiparameterization options (WT-Noah-MP) is used to numerically “tag” water from MCS and non-MCS rainfall separately during April–August (1997–2018) and track their transit in the terrestrial system. From the water-tagging results, over 50% of warm-season rainfall leaves the surface–subsurface system through evapotranspiration by the end of August, but non-MCS rainfall contributes a larger fraction. However, MCS rainfall plays a more important role in generating surface runoff. These differences are mostly attributed to the rainfall intensity differences. The higher-intensity MCS rainfall tends to produce more surface runoff through infiltration excess flow and drives a deeper penetration of the rainwater into the soil. Over 70% of the top 10th percentile runoff is contributed by MCS rainfall, demonstrating its important contribution to local flooding. In contrast, lower-intensity non-MCS rainfall resides mostly in the top layer and contributes more to evapotranspiration through soil evaporation. Diurnal timing of rainfall has negligible effects on the flux partitioning for both MCS and non-MCS rainfall. Differences in soil moisture profiles for MCS and non-MCS rainfall and the resultant evapotranspiration suggest differences in their roles in soil moisture–precipitation feedbacks and ecohydrology.


2018 ◽  
Author(s):  
Sara Sadri ◽  
Eric F. Wood ◽  
Ming Pan

Abstract. Since April 2015, NASA's Soil Moisture Active Passive (SMAP) mission has monitored near-surface soil moisture, mapping the globe between the latitude bands of 85.044° N/S in 2–3 days depending on location. SMAP Level 3 passive radiometer product (SPL3SMP) measures the amount of water in the top 5 cm of soil except for regions of heavy vegetation (vegetation water content >4.5 kg/m2) and frozen or snow covered locations. SPL3SMP retrievals are spatially and temporally discontinuous, so the 33 months offers a short SMAP record length and poses a statistical challenge for meaningful assessment of its indices. The SMAP SPL4SMAU data product provides global surface and root zone soil moisture at 9-km resolution based on assimilating the SPL3SMP product into the NASA Catchment land surface model. Of particular interest to SMAP-based agricultural applications is a monitoring product that assesses the SMAP near-surface soil moisture in terms of probability percentiles for dry and wet conditions. We describe here SMAP-based indices over the continental United States (CONUS) based on both near-surface and root zone soil moisture percentiles. The percentiles are based on fitting a Beta distribution to the retrieved moisture values. To assess the data adequacy, a statistical comparison is made between fitting the distribution to VIC soil moisture values for the days when SPL3SMP are available, versus fitting to a 1979–2017 VIC data record. For the cold season (November–April), 57 % of grids were deemed to be consistent between the periods, and 68 % in the warm season (May–October), based on a Kolmogorov–Smirnov statistical test. It is assumed that if grids passed the consistency test using VIC data, then the grid had sufficient SMAP data. Our near-surface and root zone drought index on maps are shown to be similar to those produced by the U.S. Drought Monitor (from D0-D4) and GRACE. In a similar manner, we extend the index to include pluvial conditions using indices W0-W4. This study is a step forward towards building a national and international soil moisture monitoring system, without which, quantitative measures of drought and pluvial conditions will remain difficult to judge.


2012 ◽  
Vol 27 (2) ◽  
pp. 297-303 ◽  
Author(s):  
Helin Wei ◽  
Youlong Xia ◽  
Kenneth E. Mitchell ◽  
Michael B. Ek

2008 ◽  
Vol 136 (7) ◽  
pp. 2321-2343 ◽  
Author(s):  
S. B. Trier ◽  
F. Chen ◽  
K. W. Manning ◽  
M. A. LeMone ◽  
C. A. Davis

Abstract A coupled land surface–atmospheric model that permits grid-resolved deep convection is used to examine linkages between land surface conditions, the planetary boundary layer (PBL), and precipitation during a 12-day warm-season period over the central United States. The period of study (9–21 June 2002) coincided with an extensive dry soil moisture anomaly over the western United States and adjacent high plains and wetter-than-normal soil conditions over parts of the Midwest. A range of possible atmospheric responses to soil wetness is diagnosed from a set of simulations that use land surface models (LSMs) of varying sophistication and initial land surface conditions of varying resolution and specificity to the period of study. Results suggest that the choice of LSM [Noah or the less sophisticated simple slab soil model (SLAB)] significantly influences the diurnal cycle of near-surface potential temperature and water vapor mixing ratio. The initial soil wetness also has a major impact on these thermodynamic variables, particularly during and immediately following the most intense phase of daytime surface heating. The soil wetness influences the daytime PBL evolution through both local and upstream surface evaporation and sensible heat fluxes, and through differences in the mesoscale vertical circulation that develops in response to horizontal gradients of the latter. Resulting differences in late afternoon PBL moist static energy and stability near the PBL top are associated with differences in subsequent late afternoon and evening precipitation in locations where the initial soil wetness differs among simulations. In contrast to the initial soil wetness, soil moisture evolution has negligible effects on the mean regional-scale thermodynamic conditions and precipitation during the 12-day period.


2020 ◽  
Vol 21 (1) ◽  
pp. 143-159
Author(s):  
Christine M. Albano ◽  
Michael D. Dettinger ◽  
Adrian A. Harpold

AbstractAtmospheric rivers (ARs) significantly influence precipitation and hydrologic variability in many areas of the world, including the western United States. As ARs are increasingly recognized by the research community and the public, there is a need to more precisely quantify and communicate their hydrologic impacts, which can vary from hazardous to beneficial depending on location and on the atmospheric and land surface conditions prior to and during the AR. This study leverages 33 years of atmospheric and hydrologic data for the western United States to 1) identify how water vapor amount, wind direction and speed, temperature, and antecedent soil moisture conditions influence precipitation and hydrologic responses (runoff, recharge, and snowpack) using quantile regression and 2) identify differences in hydrologic response types and magnitudes across the study region. Results indicate that water vapor amount serves as a primary control on precipitation amounts. Holding water vapor constant, precipitation amounts vary with wind direction, depending on location, and are consistently greater at colder temperatures. Runoff efficiencies further covary with temperature and antecedent soil moisture, with precipitation falling as snow and greater available water storage in the soil column mitigating flood impacts of large AR events. This study identifies the coastal and maritime mountain ranges as areas with the greatest potential for hazardous flooding and snowfall impacts. This spatially explicit information can lead to better understanding of the conditions under which ARs of different precipitation amounts are likely to be hazardous at a given location.


2006 ◽  
Vol 21 (5) ◽  
pp. 869-892 ◽  
Author(s):  
David T. Myrick ◽  
John D. Horel

Abstract Experimental gridded forecasts of surface temperature issued by National Weather Service offices in the western United States during the 2003/04 winter season (18 November 2003–29 February 2004) are evaluated relative to surface observations and gridded analyses. The 5-km horizontal resolution gridded forecasts issued at 0000 UTC for forecast lead times at 12-h intervals from 12 to 168 h were obtained from the National Digital Forecast Database (NDFD). Forecast accuracy and skill are determined relative to observations at over 3000 locations archived by MesoWest. Forecast quality is also determined relative to Rapid Update Cycle (RUC) analyses at 20-km resolution that are interpolated to the 5-km NDFD grid as well as objective analyses obtained from the Advanced Regional Prediction System Data Assimilation System that rely upon the MesoWest observations and RUC analyses. For the West as a whole, the experimental temperature forecasts issued at 0000 UTC during the 2003/04 winter season exhibit skill at lead times of 12, 24, 36, and 48 h on the basis of several verification approaches. Subgrid-scale temperature variations and observational and analysis errors undoubtedly contribute some uncertainty regarding these results. Even though the “true” values appropriate to evaluate the forecast values on the NDFD grid are unknown, it is estimated that the root-mean-square errors of the NDFD temperature forecasts are on the order of 3°C at lead times shorter than 48 h and greater than 4°C at lead times longer than 120 h. However, such estimates are derived from only a small fraction of the NDFD grid boxes. Incremental improvements in forecast accuracy as a result of forecaster adjustments to the 0000 UTC temperature grids from 144- to 24-h lead times are estimated to be on the order of 13%.


2020 ◽  
Author(s):  
Yanping Li ◽  
Zhe Zhang ◽  
Micheal Barlage ◽  
Fei Chen ◽  
Warren Helgason ◽  
...  

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