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Rasool Porhemmat, Heather Purdie, Peyman Zawar-Reza, Christian Zammit, and Tim Kerr

prediction models to produce atmospheric reanalysis data ( Lavers et al. 2012 ). ERA-Interim data were retrieved at 6-hourly temporal resolution and 0.5° × 0.5° spatial resolution for a geographic window spanning of 10°–60°S and 130°E–160°W (see Fig. 1b ). The data used in this study include sea level pressure (SLP; hPa), geopotential height at 500 hPa (Z500; m), temperature ( T ; °C), specific humidity ( q ; g kg −1 ), specific cloud ice water content (g kg −1 ), zonal and meridional wind fields ( u

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Rui Mei, Guiling Wang, and Huanghe Gu

-Emanuel scheme ( Emanuel 1991 ); and the land surface process described by the Biosphere–Atmosphere Transfer Scheme (BATS; Dickinson et al. 1993 ). RegCM4 differs from RegCM3 with the following major improvements: a prognostic SST scheme ( Zeng and Beljaars 2005 ) was implemented to improve the calculation of diurnal fluxes over the ocean, sea ice was introduced in SST boundary conditions, aerosol and dust models were improved following Laurent et al. (2008) and Alfaro and Gomes (2001) , and Community

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Klaus Vormoor and Thomas Skaugen

because of the coarse spatial resolution of the model. Temperature in a HIRLAM grid cell depends on its most dominant land cover type (water, ice, bedrock, low vegetation, or wood). Furuneset is physically located on a peninsula in the North Sea. The HIRLAM grid cell that covers Furuneset, however, is probably characterized by dominating bedrock and low vegetation cover, which would lead to an overestimation of continentality. The tendency to underestimate low temperatures and overestimate high

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Liang Chen, Trent W. Ford, and Priyanka Yadav

atmosphere, ocean, land, sea ice, and land ice. As the primary focus of this study is flash drought and land–atmosphere feedback, all the simulations are conducted with the FHIST component set. The FHIST component set allows the active, coupled Community Atmosphere Model (CAM6; Bogenschutz et al. 2018 ) and Community Land Model (CLM5; Lawrence et al. 2019 ) but using prescribed transient monthly sea surface temperatures (SSTs) and sea ice concentrations (SICs). The transient SSTs and SICs are derived

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Jinwoong Yoo, Joseph A. Santanello Jr., Marshall Shepherd, Sujay Kumar, Patricia Lawston, and Andrew M. Thomas

records, yielding a 6-hourly dataset for the storm period of interest from 0000 UTC 16 February to 0000 UTC 20 February (see the online supplemental material for multiple track observation dataset comparison). The NOAA/National Centers for Environmental Information (NCEI) optimum interpolation (OI) sea surface temperature (SST) dataset ( https://www.ncdc.noaa.gov/oisst/data-access ; Fig. 1a ) suggests that warm SST favorable for TC development (>26°C or 299 K) was prevalent off the northern coast of

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Paul A. Dirmeyer, Yan Jin, Bohar Singh, and Xiaoqin Yan

the individual models quite well, without loss of information by smoothing of some data to a lower resolution or a spatially shifted grid of similar resolution. We also project the land–sea ice mask of each model onto this high-resolution grid and only retain for comparison the points on the high-resolution grid where the fraction of land points across all models exceeds 80%. This approach appears to do a good job of retaining the coastlines of the continents, although all but the largest islands

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Seyed-Mohammad Hosseini-Moghari and Qiuhong Tang

( Behrangi et al. 2014b ; Mehran and AghaKouchak 2014 ; Shige et al. 2013 ; Sorooshian et al. 2011 ). Actually, in the case of warm orographic rainfall, infrared sensors have limited ability for detecting rainfall when the cloud tops are warmer than the temperature thresholds of the sensors. And microwave sensors estimate rainfall rate based on the scattering by ice particles, which can noticeably cause underestimation ( Rafiuddin et al. 2010 ). Over the south of the Caspian Sea, no significant

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Marouane Temimi, Ricardo Fonseca, Narendra Nelli, Michael Weston, Mohan Thota, Vineeth Valappil, Oliver Branch, Hans-Dieter Wizemann, Niranjan Kumar Kondapalli, Youssef Wehbe, Taha Al Hosary, Abdeltawab Shalaby, Noor Al Shamsi, and Hajer Al Naqbi

: A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 113 pp., https://doi.org/10.5065/D68S4MVH . 10.5065/D68S4MVH Sukoriansky , S. , B. Galperin , and V. Perov , 2005 : Application of a new spectral model of stratified turbulence to the atmospheric boundary layer over sea ice . Bound.-Layer Meteor. , 117 , 231 – 257 , https://doi.org/10.1007/s10546-004-6848-4 . 10.1007/s10546-004-6848-4 Sun , L. , and K. Schulz , 2015 : The improvement of

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Muattar Saydi, Guoping Tang, Yan Qin, Hong Fang, and Xiaohua Chen

snowfall in the arid Central Asia; a high correlation, which is 0.51 and significant at the 99% confidence level, verifies their link ( Huang et al. 2013 ). Also, the recession in Arctic sea ice cover has played a significant role in supporting increased snowfall in the arid Central Asia ( Huang et al. 2015a ), probably because reduction of sea ice provides excessive moisture flux ( Liu et al. 2012 ). In addition, the enhanced pressure gradient caused by the North Atlantic Oscillation ( Huang et al

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Zhe Zhang, Youcun Qi, Donghuan Li, Ziwei Zhu, Meilin Yang, Nan Wang, Yin Yang, and Qiyuan Hu

precipitation systems ( Biggerstaff and Houze 1993 ; Cifelli et al. 2000 ; Houze 2004 ). For example, most stratiform clouds are formed above the 0°C height so that the ice-phase microphysical processes are crucial in stratiform precipitation. When the ice phase particles fall below the 0°C level, the melting phase of ice particles can enhance the radar reflectivity and a bright band (BB) feature could be evident in radar echoes. Compared to stratiform precipitation, the precipitation processes in the

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