Satellite snow cover area (SCA) mapping using optical sensors has been known to suffer severe obstruction due to vegetation canopy and cloud cover. Several algorithms have been developed to reduce cloud cover contamination and enhance the SCA mapping. In this study we introduce the use of a daily SCA product from the Multisensor Snow and Ice Mapping System (IMS) at a nominal resolution of 4 km, assess its accuracy and error levels against in situ observations, and compare the IMS SCA product with the SCA products from moderate resolution imaging spectroradiometer (MODIS), a combination of daily Terra and Aqua satellites. The results show that the snow accuracies are higher during winter for both IMS and MODIS, and that there is not much difference between MODIS at 500 m and upscaled at 4 km. The IMS SCA mapping accuracies are significantly higher than MODIS accuracies for all sky conditions, while they are similar to or slightly lower than MODIS accuracies in clear sky conditions. The overestimate error of snow cover using IMS is higher (lower) than that of MODIS during ablation (accumulation) periods. Both MODIS and IMS show a similar pattern of underestimation errors of snow cover with the IMS being slightly higher than the MODIS. It is concluded that the IMS SCA product has potential as a good alternative for the MODIS daily SCA products or replacing those cloud pixels in the MODIS daily or multiday products.
This study examines precipitation accumulation and intensity trends across a region in southwest Saudi Arabia characterized by distinct seasonal weather patterns and mountainous terrain. The region is an example of an arid/semiarid area faced with maintaining sustainable water resources with a growing population. Annual and seasonal trends in precipitation amount were examined from 29 rain gages divided among four geographically unique regions from 1945/1946 to 2009. Two of the regions displayed significantly declining annual trends over the time series using a Mann‐Kendall test modified for autocorrelation (α < 0.05). Seasonal analysis revealed insignificant declining trends in at least two of the regions during each season. The largest and most consistent declining trends occurred during wintertime where all regions experienced negative trends. Several intensity metrics were examined in the study area from four additional stations containing daily data from 1985 to 2011. Intensity metrics included total precipitation, wet day count, simple intensity index, maximum daily annual rainfall, and upper/lower precipitation distribution changes. In general, no coherent trends were found among the daily stations suggesting precipitation is intensifying across the study area. The work represents the first of its size in the study area, and one of few in the region due to the lack of available long‐term data needed to properly examine precipitation changes.
Heavy rainfall and flooding associated with Tropical Storm Hermine occurred on 7-8 September 2010 across central Texas, resulting in several flood-related fatalities and extensive property damage. The largest rainfall totals were received near Austin, Texas, and immediately north, with 24-h accumulations at several locations reaching a 500-yr recurrence interval. Among the most heavily impacted drainage basins was the Bull Creek watershed (58 km 2 ) in Austin, where peak flows exceeded 500 m 3 s 21 . Storm cells were trained over the small watershed for approximately 6 h because of the combination of a quasi-stationary synoptic feature slowing the storm, orographic enhancement from the Balcones Escarpment, and moist air masses from the Gulf of Mexico sustaining the storm. Weather Research and Forecasting Model simulations with and without the Balcones Escarpment terrain indicate that orographic enhancement affected rainfall. The basin received nearly 300 mm of precipitation, with maximum sustained intensities of 50 mm h 21 . The Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model was used to simulate streamflow from the event and to analyze the flood hydrology. Model simulations indicate that the spatial organization of the storm during intense rainfall periods coupled with surface conditions and characteristics mediate stream response.
Two years of K-Band micro rain radar-2 (MRR) data are used to investigate the vertical variability of rain in an atmospheric column and assess MRR rainfall estimates accuracy from both direct rainfall measurement using the Mie Theory (i.e., MRR RR) and a Z-R relationship (Z = 300 R1.4) (i.e., MRR Rz). Two different height resolutions (HR) settings are used. A nearby Doppler weather radar KEWX (S-band) using the same Z-R relationship is found to underestimate rainfall by up to 32.2%, while MRR estimates are much closer to collocated gauge measurements. For the first three gates, MRR RR underestimates rainfall by 5.7%–60.1% for the HR of 35 meters and by 31.2%–47.9% for the 100 meter resolution, while MRR RR overestimates rainfall for higher gates at the 100 m resolution, and MRR Rz underestimates rainfall at all gates due to errors of the Z-R relationship (Z = aRb). Gates higher than 2,000 m are affected by bright band and mixed phase rainfall. Examination of the rainfall statistics suggests that the 100 m HR produces better rainfall estimates, and that the gate centered at 300 m has better performance than the gate centered at 70 m.
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