Assimilation of Ocean Surface Wind Data by the HY-2B Satellite in GRAPES: Impacts on Analyses and Forecasts

The ocean surface wind(OSW)data retrieved from microwave scatterometers have high spatial accuracy and represent the only wind data assimilated by global numerical models on the ocean surface,thus playing an important role in improving the forecast skills of global medium-range weather prediction models.To improve the forecast skills of the Global/Regional Assimilation and Prediction System Global Forecast System(GRAPES_GFS),the HY-2B OSW data is assimilated into the GRAPES_GFS four-dimensional variational assimilation(4DVAR)system.Then,the impacts of the HY-2B OSW data assimilation on the analyses and forecasts of GRAPES_GFS are analyzed based on one-month assimilation cycle experiments.The results show that after assimilating the HY-2B OSW data,the analysis errors of the wind fields in the lower-middle troposphere(1000-600 hPa)of the tropics and the southern hemisphere(SH)are significantly reduced by an average rate of about 5%.The impacts of the HY-2B OSW data assimilation on the analysis fields of wind,geopotential height,and temperature are not solely limited to the boundary layer but also extend throughout the entire troposphere after about two days of cycling assimilation.Furthermore,assimilating the HY-2B OSW data can significantly improve the forecast skill of wind,geopotential height,and temperature in the troposphere of the tropics and SH.

Annual and Interannual Variability of Scatterometer Ocean Surface Wind over the South China Sea

To investigate the annual and interaunual variability of ocean surface wind over the South China Sea （SCS）, the vector empirical orthogonal function （VEOF） method and the Hilbert-Huang transform （HHT） method were employed to analyze a set of combined satellite scatterometer wind data during the period from December 1992 to October 2009. The merged wind data were generated from European Remote Sensing Satellite （ERS）-1/2 Scatterometer, NASA Scatterometer （NSCAT） and NASA＇s Quick Scatterometer （QuikSCAT） wind products. The first VEOF mode corresponds to a winter-summer mode which accounts for 87.3% of the total variance and represents the East Asian monsoon features. The second mode of VEOF corresponds to a spring-autumn oscil- lation which accounts for 8.3% of the total variance. To analyze the interannual variability, the annual signal was removed from the wind data set and the VEOFs of the residuals were calculated. The temporal mode of the ftrst intcrannual VEOF is correlated with the Southern Oscillation Index （SOI） with a four-month lag. The second temporal interannual VEOF mode is correlated with the SOI with no time lag. The time series of the two interannual VEOFs were decomposed using the HI-IT method and the results also show a correlation between the interannual variability and El Nino-Southern Oscillation （ENSO） events.

Identification and Interpretation of Earth’s Atmosphere Dynamics’ and Thermodynamics’ Similarities between Rogue Waves and Oceans’ Surface Geostrophic Wind

In their daily practices, meteorologists make extensive use of the geostrophic wind properties to explain many weather phenomena such as the meaning and direction of the horizontal winds that take place around the low atmospheric pressures. The biggest challenge that faces the public who is interested in information disseminated by meteorologists is to know exactly what means the geostrophic wind. Besides the literal definitions scattered in very little scientific work, there is unfortunately no book which gives importance to the algebraic definition of the geostrophic wind. Our work shows that to better understand the behavior of natural phenomena, it is essential to combine the theories with based observations. Obviously, observations cannot be relevant without a theory that guides the observers. Conversely, no theory can be validated without experimental verification. Synoptic observations show that in the “free atmosphere!” the wind vectors are very nearly parallel to isobars, and the flow is perpendicular to the horizontal pressure gradient force, at least at any given instant. This kind of information recommends great caution when making geostrophic approximations. Our work also shows that for tornadoes, there is no need to move away from the surface of the oceans to observe the geostrophic balance. Undoubtedly, identification and interpretation of earth’s atmosphere dynamics’ and thermodynamics’ similarities between rogue waves and oceans’ surface geostrophic wind will be an easy exercise to researchers who will give importance to result provided by this paper.

Applications of AMSR-E Measurements for Tropical Cyclone Predictions PartⅠ: Retrieval of Sea Surface Temperature and Wind Speed

Existing satellite microwave algorithms for retrieving Sea Surface Temperature （SST） and Wind （SSW） are applicable primarily for non-raining cloudy conditions. With the launch of the Earth Observing System （EOS） Aqua satellite in 2002, the Advanced Microwave Scanning Radiometer （AMSRoE） onboard provides some unique measurements at lower frequencies which are sensitive to ocean surface parameters under adverse weather conditions. In this study, a new algorithm is developed to derive SST and SSW for hurricane predictions such as hurricane vortex analysis from the AMSRoE measurements at 6.925 and 10.65 GHz. In the algorithm, the effects of precipitation emission and scattering on the measurements are properly taken into account. The algorithm performances are evaluated with buoy measurements and aircraft dropsonde data. It is found that the root mean square （RMS） errors for SST and SSW are about 1.8 K and 1.9 m s^- 1, respectively, when the results are compared with the buoy data over open oceans under precipitating clouds （e.g., its liquid water path is larger than 0.5 mm）, while they are 1.1 K for SST and 2.0 m s^-1 for SSW, respectively, when the retrievals are validated against the dropsonde measurements over warm oceans. These results indicate that our newly developed algorithm can provide some critical surface information for tropical cycle predictions. Currently, this newly developed algorithm has been implemented into the hybrid variational scheme for the hurricane vortex analysis to provide predictions of SST and SSW fields.

Tropical Cyclone Ocean Winds and Structure Parameters Retrieved from Cross-Polarized SAR Measurements

Spaceborne synthetic aperture radar(SAR)can provide unique capabilities to measure ocean surface winds under tropical cyclones(TCs),on synoptic scales,and at a very high spatial resolution.In this paper,we first discuss the accuracy and reliability of SAR-retrieved TC marine winds.The results show that wind retrievals from SAR images are in good agreement with Stepped Frequency Microwave Radiometer(SFMR)measurements,with root-mean-square error(RMSE)and correlation coefficient(CC)of 3.52 m s^(−1) and 0.91,respectively.Based on the marine winds retrieved from SAR images,a relatively simple method is applied to extract the storm intensity(maximum wind speed)and wind radii(R34,R50,and R64)from 234 cross-polarized SAR images,in the Northwest Pacific Ocean from 2015 to 2023.The SAR-retrieved TC wind radii and intensities are compared with the best-track reports,with RMSEs for R34,R50,and R64 being 48.32,41.88,and 38.51 km,and CCs being 0.87,0.83,and 0.65,respectively.In terms of TC intensity,the RMSE and bias between SAR estimates and best-track data are 7.32 and 0.38 m s^(−1),respectively.For TC Surigae(2023),we found that employing a combination of multiplatform SARs,acquired within a short time interval,has the potential to simultaneously measure the intensity and wind structure parameters.In addition,for a storm with a long life cycle,the multitemporal synergistic SARs can be used to investigate fine-scale features of the TC ocean winds,as well as the evolution of TC surface wind intensities and wind structures.

Wind speed inversion and in-orbit assessment of the imaging altimeter on Tiangong-2 space station

Imaging altimeter(IALT)is a new type of radar altimeter system.In contrast to the conventional nadir-looking altimeters,such as HY-2 A altimeter,Jason-1/2,and TOPEX/Poseidon,IALT observes the earth surface at low incident angles(2.5°–8°),so its swath is much wider and its spatial resolution is much higher than the previous altimeters.This paper presents a wind speed inversion method for the recently launched IALT onboard Tiangong-2 space station.Since the current calibration results of IALT do not agree well with the well-known wind geophysical model function at low incidence angles,a neural network is used to retrieve the ocean surface wind speed in this study.The wind speed inversion accuracy is evaluated by comparing with the ECMWF reanalysis wind speed,buoy wind speed,and in-situ ship measurements.The results show that the retrieved wind speed bias is about–0.21 m/s,and the root-mean-square(RMS)error is about 1.85 m/s.The wind speed accuracy of IALT meets the performance requirement.

Evolution of the 2015/16 El Nio and historical perspective since 1979

The 2015/16 El Nio developed from weak warm conditions in late 2014 and NINO3.4 reached 3℃ in November 2015. We describe the characteristics of the evolution of the 2015/16 El Nio using various data sets including SST, surface winds,outgoing longwave radiation and subsurface temperature from an ensemble operational ocean reanalyses, and place this event in the context of historical ENSO events since 1979. One salient feature about the 2015/16 El Nio was a large number of westerly wind bursts and downwelling oceanic Kelvin waves(DWKVs). Four DWKVs were observed in April-November 2015 that initiated and enhanced the eastern-central Pacific warming. Eastward zonal current anomalies associated with DWKVs advected the warm pool water eastward in spring/summer. An upwelling Kelvin wave(UWKV) emerged in early November 2015 leading to a rapid decline of the event. Another outstanding feature was that NINO4 reached a historical high(1.7℃), which was 1℃(0.8℃) higher than that of the 1982/83(1997/98) El Nio . Although NINO3 was comparable to that of the 1982/83 and 1997/98 El Nio , NINO1+2 was much weaker. Consistently, enhanced convection was displaced 20 degree westward, and the maximum D20 anomaly was about 1/3.1/2 of that in 1997 and 1982 near the west coast of South America.