Atmospheric frontal gravity waves observed in satellite SAR images of the Bohai Sea and Huanghai Sea

In the satellite synthetic aperture radar（SAR） images of the Bohai Sea and Huanghai Sea,the authors observe sea surface imprints of wave-like patterns with an average wavelength of 3.8 km.Comparing SAR observations with sea surface wind fields and surface weather maps,the authors find that the occurrence of the wave-like phenomena is associated with the passing of atmospheric front.The authors define the waves as atmospheric frontal gravity waves.The dynamical parameters of the wave packets are derived from statistics of 9 satellite SAR images obtained from 2002 to 2008.A two-dimensional linear physical wave model is used to analyze the generation mechanism of the waves.The atmospheric frontal wave induced wind variation across the frontal wave packet is compared with wind retrievals from the SAR images.The CMOD-5（C-band scatterometer ocean geophysical model function） is used for SAR wind retrievals VV（transmitted vertical and received vertical） for ENVISAT and HH（transmitted horizontally and received horizontally） for RADARSAT-1.A reasonable agreement between the analytical solution and the SAR observation is reached.This new SAR frontal wave observation adds to the school of SAR observations of sea surface imprints of AGWs including island lee waves,coastal lee waves,and upstream Atmospheric Gravity Waves（AGW）.

Scale-dependent Regional Climate Predictability over North America Inferred from CMIP3 and CMIP5 Ensemble Simulations

Through the analysis of ensembles of coupled model simulations and projections collected from CMIP3 and CMIP5, we demonstrate that a fundamental spatial scale limit might exist below which useful additional refinement of climate model predictions and projections may not be possible. That limit varies among climate variables and from region to region. We show that the uncertainty（noise） in surface temperature predictions（represented by the spread among an ensemble of global climate model simulations） generally exceeds the ensemble mean（signal） at horizontal scales below 1000 km throughout North America, implying poor predictability at those scales. More limited skill is shown for the predictability of regional precipitation. The ensemble spread in this case tends to exceed or equal the ensemble mean for scales below 2000 km. These findings highlight the challenges in predicting regionally specific future climate anomalies, especially for hydroclimatic impacts such as drought and wetness.

Coastal upwelling observed by multi-satellite sensors

Coastal upwelling phenomenon along the China coast in the Yellow Sea during August 2007 is studied using ENVISAT Advanced Synthetic Aperture Radar (ASAR) data, NOAA Advanced AVHRR series Sea Surface Temperature (SST) data,and NASA QuikSCAT Scatterometer ocean surface wind data. A dark pattern in an ASAR image is interpreted as coastal upwelling. This is because the natural biogenic slicks associated with coastal upwelling damp the Bragg waves on the sea surface and thus make the surface smoother. Most of the incoming radar energy is reflected in the forward direction. As a result, the radar backscatter signal is very weak. Analyzing the concurrent AVHRR SST image, we find that the dark pattern in the ASAR image is indeed corresponding to the low SST area. The wind retrieval in the slicks dominant region is biased due to the low Normalised Radar Cross Section (NRCS) associated with the coastal upwelling. We applied a SST correction to the NRCS values to improve the accuracy of wind retrieval from ASAR data.

ADVANCING THE STATE OF THE ART IN OPERATIONAL TROPICAL CYCLONE FORECASTING AT NCEP

Regional Hurricane modeling systems developed and implemented into operations at National Centers for Environmental Prediction(NCEP)of National Oceanic and Atmospheric Administration(NOAA)National Weather Service(NWS)are now used for tropical cyclone forecast guidance in all ocean basins of the world.Lately,HWRF(Hurricane Weather Research and Forecast)modeling system has made significant improvements to the state of the art in numerical guidance for tropical cyclone track,intensity,size,structure and rainfall forecasts.These improvements come from advances in various components of the modeling system that are incorporated into the model in yearly upgrade cycles.NWS/NCEP/Environmental Modeling Center’s hurricane team has also developed another non-hydrostatic hurricane model in NOAA Environmental Modeling System(NEMS)framework known as HMON(Hurricanes in a Multi-scale Ocean-coupled Non-hydrostatic)model which was implemented at NCEP operations this past year.Development of HMON is consistent with,and a step closer to developing Next Generation Global Prediction System(NGGPS)chosen Finite Volume Cubed-Sphere(FV3)dynamic core based global to local scale coupled models in a unified modeling framework.In this paper,operational configuration details of this new HMON model are discussed along with operational HWRF model upgrades,and their forecast performance is compared to other models.We also discuss plans for hurricane model improvements in the next two to five years.