Agnes H. N. Lim

Assimilation of clear sky Atmospheric Infrared Sounder radiances in short-term regional forecasts using community models

Abstract Regional assimilation experiments of clear-sky Atmospheric Infrared Sounder (AIRS) radiances were performed using the gridpoint statistical interpolation three-dimensional variational assimilation system coupled to the weather research and forecasting model. The data assimilation system and forecast model used in this study are separate community models; it cannot be assumed that the coupled systems work optimally. Tuning was performed on the data assimilation system and forecast model. Components tuned included the background error covariance matrix, the satellite radiance bias correction, the quality control procedures for AIRS radiances, the forecast model resolution, and the infrared channel selection. Assimilation metrics and diagnostics from the assimilation system were used to identify problems when combining separate systems. Forecasts initiated from analyses after assimilation were verified with model analyses, rawinsondes, nonassimilated satellite radiances, and 24 h–accumulated precipitation. Assimilation of clear sky AIRS radiances showed the largest improvement in temperature and radiance brightness temperature bias when compared with rawinsondes and satellite observations, respectively. Precipitation skill scores displayed minor changes with AIRS radiance assimilation. The 00 and 12 coordinated universal time (UTC) forecasts were typically of better quality than the 06 and 18 UTC forecasts, possibly due to the amount of AIRS data available for each assimilation cycle.

Tuning of background error statistics through sensitivity experiments and its impact on typhoon forecast

Abstract. Background error covariance (B) matrix is critical for variational data assimilation as it greatly affects the analyses of three-dimensional variational assimilation. The National Meteorological Center method was used to estimate the B matrix using the forecasts from the Advanced Research Weather Research and Forecasting regional model. To further understand and evaluate the newly generated regional B matrix, its characteristics were compared with the global B estimated from the Global Forecast System model. Sensitivity experiments were undertaken by changing the horizontal length-scales and standard deviations of the B matrix, and its impacts on the typhoon forecast were also examined. Verification against radiosonde observations showed that the varying horizontal length-scale has a significant positive impact on the 24-h forecast of temperature, specific humidity, u-wind, and v-wind. On the other hand, changing standard deviations of the B matrix has a slight influence only on the specific humidity and wind (u-component) forecast. Compared with the global B, the tuned regional B showed improvements in temperature forecasts. In addition, using the tuned regional B also led to a positive impact on the typhoon (Saola, Damrey, and Haikui) track forecasts as compared with the untuned B and global B.

The Impact of Cross‐track Infrared Sounder (CrIS) Cloud‐Cleared Radiances on Hurricane Joaquin (2015) and Matthew (2016) Forecasts

Hyperspectral infrared (IR) sounders provide high vertical resolution atmospheric sounding information that can improve the forecast skill in numerical weather prediction. Commonly, only clear radiances are assimilated, because IR sounder observations are highly affected by clouds. A cloud-clearing (CC) technique, which removes the cloud effects from an IR cloudy field of view (FOV) and derives the cloud-cleared radiances (CCRs) or clear-sky equivalent radiances, can be an alternative yet effective way to take advantage of the thermodynamic information from cloudy skies in data assimilation. This study develops a Visible Infrared Imaging Radiometer Suite (VIIRS)-based CC method for deriving Cross-track Infrared Sounder (CrIS) CCRs under partially cloudy conditions. Due to the lack of absorption bands on VIIRS, two important quality control steps are implemented in the CC process. Validation using VIIRS clear radiances indicates that the CC method can effectively obtain the CrIS CCRs for FOVs with partial cloud cover. To compare the impacts from assimilation of CrIS original radiances and CCRs, three experiments are carried out on two storm cases, Hurricane Joaquin (2015) and Hurricane Matthew (2016), using Gridpoint Statistical Interpolation assimilation system and Weather Research and Forecasting-Advanced Research Version models. At the analysis time, more CrIS observations are assimilated when using CrIS CCRs than with CrIS original radiances. Comparing temperature, specific humidity, and U/V winds with radiosondes indicates that the data impacts are growing larger with longer time forecasts (beyond 72 h forecast). Hurricane track forecasts also show improvements from the assimilation of CrIS CCRs due to better weather system forecasts. The impacts of CCRs on intensity are basically neutral with mixed positive and negative results.

Value-added Impact of Geostationary Hyperspectral Infrared Sounders on Local Severe Storm Forecasts—via a Quick Regional OSSE

Accurate atmospheric temperature and moisture information with high temporal/spatial resolutions are two of the key parameters needed in regional numerical weather prediction (NWP) models to reliably predict high-impact weather events such as local severe storms (LSSs). High spectral resolution or hyperspectral infrared (HIR) sounders from geostationary orbit (GEO) provide an unprecedented source of near time-continuous, three-dimensional information on the dynamic and thermodynamic atmospheric fields—an important benefit for nowcasting and NWP-based forecasting. In order to demonstrate the value of GEO HIR sounder radiances on LSS forecasts, a quick regional OSSE (Observing System Simulation Experiment) framework has been developed, including high-resolution nature run generation, synthetic observation simulation and validation, and impact study on LSS forecasts. Results show that, on top of the existing LEO (low earth orbit) sounders, a GEO HIR sounder may provide value-added impact [a reduction of 3.56% in normalized root-mean-square difference (RMSD)] on LSS forecasts due to large spatial coverage and high temporal resolution, even though the data are assimilated every 6 h with a thinning of 60 km. Additionally, more frequent assimilations and smaller thinning distances allow more observations to be assimilated, and may further increase the positive impact from a GEO HIR sounder. On the other hand, with denser and more frequent observations assimilated, it becomes more difficult to handle the spatial error correlation in observations and gravity waves due to the limitations of current assimilation and forecast systems (such as a static background error covariance). The peak reduction of 4.6% in normalized RMSD is found when observations are assimilated every 3 h with a thinning distance of 30 km.摘 要具有高时空间分辨率的精确的大气温度和湿度信息, 是利用区域数值天气预报模式, 准确预报局地强风暴天气的两个关键参数. 来自地球静止轨道的高光谱分辨率红外探测仪, 能提供大气的动力和热力的近乎连续的三维信息. 这些前所未有的关于大气垂直结构的信息, 对临近预报和基于数值天气模式的预报具有重要意义. 为了展示地球静止轨道高光谱红外探测仪对局地强风暴预报的价值, 我们开发了一个快速的区域观测系统模拟试验框架, 包括高分辨率的自然大气场景(nature run)的生成, 观测的模拟和验证, 以及对局地强风暴预报的影响研究. 结果表明, 与现有的低地球轨道大气探测仪的相比, 地球静止轨道高光谱红外探测仪对区域模式具有更大的空间覆盖率和更高的时间分辨率. 在目前的每6小时一次, 稀疏距离为60公里的业务同化设置下, 能够改进局地强风暴预报, 减少整体分析和预报误差3.56%. 此外, 更频繁的同化和更小的数据稀疏距离能使更多的观测数据被同化, 从而进一步增加地球静止轨道高光谱红外探测仪的正影响效果.

Radiance Preprocessing for Assimilation in the Hourly Updating Rapid Refresh Mesoscale Model: A Study Using AIRS Data

AbstractThis study describes the initial application of radiance bias correction and channel selection in the hourly updated Rapid Refresh model. For this initial application, data from the Atmospheric Infrared Sounder (AIRS) are used; this dataset gives atmospheric temperature and water vapor information at higher vertical resolution and accuracy than previously launched low-spectral resolution satellite systems. In this preliminary study, data from AIRS are shown to add skill to short-range weather forecasts over a relatively data-rich area. Two 1-month retrospective runs were conducted to evaluate the impact of assimilating clear-sky AIRS radiance data on 1–12-h forecasts using a research version of the National Oceanic and Atmospheric Administration (NOAA) Rapid Refresh (RAP) regional mesoscale model already assimilating conventional and other radiance [AMSU-A, Microwave Humidity Sounder (MHS), HIRS-4] data. Prior to performing the assimilation, a channel selection and bias-correction spinup procedure...