Brett Candy

The Assimilation of SSMIS Radiances in Numerical Weather Prediction Models

The measurement uncertainty requirements imposed by numerical weather prediction (NWP) data assimilation applications for temperature sounding radiances are very demanding. For an ensemble of observations collected during an orbit, (postbias correction) measurement uncertainties of ~ 0.2 K (at 1 sigma) or better are required in tropospheric sounding channels to improve analyses, and hence forecasts, from current NWP models. A significant fraction of F-16 Special Sensor Microwave Imager/Sounder (SSMIS) observations are affected by calibration errors caused by solar intrusions into the warm calibration load and by thermal emission from the main reflector. The magnitude of these effects is as large as 1.5 K for the lower atmospheric temperature sounding channels. This paper describes the approach to correct for these effects, which involves data averaging, flagging solar intrusions, and modeling reflector emission. The resulting quality of the radiances is improved by a factor of three to four for mid-tropospheric temperature sounding channels. Observation minus background field differences are reduced from 0.5-0.8 K (at one standard deviation) for uncorrected data to 0.2 K for corrected data. Although localized biases remain in the corrected data, assimilation experiments using SSMIS data at four operational NWP centers (Met Office, ECMWF, NCEP, and NRL) show a neutral-to-positive impact on forecast quality in the Southern Hemisphere with, for example, mean sea-level pressure forecast errors at days 1-4 reduced by 0.5%-2.5%. Impacts in the Northern Hemisphere are neutral in most assimilation experiments.

A Comparison of the Impact of QuikScat and WindSat Wind Vector Products on Met Office Analyses and Forecasts

Several studies have demonstrated that retrievals of wind vectors from the WindSat polarimetric radiometer are of sufficient quality to be considered for assimilation in operational numerical weather prediction models. In this paper, WindSat data are used in a state-of-the-art global meteorological analysis and forecasting system. Each wind vector contains a directional ambiguity and so is assimilated in a similar way to that of scatterometer data. The forecast impact of using analyses containing information from WindSat data was investigated for a period during August and September of 2005, when a large number of tropical cyclones were present. Forecast errors were reduced in the surface pressure fields, and the average improvement across the forecast range was found to be 1.0%. This is comparable to the improvement of 1.1% found in the same fields when winds were assimilated from the QuikScat scatterometer. The impact on tropical cyclone tracks in the forecasts was also studied. The scatterometer improved (reduced) the track errors markedly by 25% in the analyses. When impacts across the forecast range out to five days were also included, the improvement was found to be 8%. In contrast, the assimilation of WindSat data improved the analysis track errors by 7%, although this figure was found to be 10% across the complete forecast range.

Monitoring Satellite Radiance Biases Using NWP Models

Radiances measured by satellite radiometers are often subject to biases due to limitations in their radiometric calibration. In support of the Global Space-based Inter-Calibration System project, to improve the quality of calibrated radiances from atmospheric sounders and imaging radiometers, an activity is underway to compare routinely measured radiances with those simulated from operational global numerical weather prediction (NWP) fields. This paper describes the results obtained from the first three years of these comparisons. Data from the High-resolution Infrared Radiation Sounder, Spinning Enhanced Visible and Infrared Imager, Advanced Along-Track Scanning Radiometer, Advanced Microwave Sounding Unit, and Microwave Humidity Sounder radiometers, together with the Atmospheric Infrared Sounder, a spectrometer, and the Infrared Atmospheric Sounding Interferometer, an interferometer, were included in the analysis. Changes in mean biases and their standard deviations were used to investigate the temporal stability of the bias and radiometric noise of the instruments. A double difference technique can be employed to remove the effect of changes or deficiencies in the NWP model which can contribute to the biases. The variation of the biases with other variables is also investigated, such as scene temperature, scan angle, location, and time of day. Many of the instruments were shown to be stable in time, with a few exceptions, but measurements from the same instrument on different platforms are often biased with respect to each other. The limitations of the polar simultaneous nadir overpasses often used to monitor biases between polar-orbiting sensors are shown with these results due to the apparent strong dependence of some radiance biases on scene temperature.

An evaluation of the potential of polarimetric radiometry for numerical weather prediction using QuikSCAT

It has been proposed that wind vector information derived from passive microwave radiometry may provide an impact on numerical weather forecasts of similar magnitude to that achieved by scatterometers. Polarimetric radiometers have a lower sensitivity to wind direction than scatterometers at low wind speed but comparable sensitivity at high windspeed. In this paper, we describe an experiment which aimed to determine if an observing system only capable of providing wind direction information at wind speeds over 8 ms/sup -1/ can provide comparable impact to one providing wind vectors at wind speeds over 2 ms/sup -1/. The QuikSCAT dataset used in the experiments has a wide swath and is used operationally by several forecast centers. The results confirm that assimilation of wind vectors from QuikSCAT only for wind speeds above 8 ms/sup -1/ gives similar analysis increments and forecast impacts to assimilating wind vectors at all wind speeds above 2 ms/sup -1/. Measurements from the WindSat five frequency polarimetric radiometer are compared with calculations from Met Office global forecast fields, and this also confirms that WindSat measurement and radiative transfer model accuracy appears to be sufficiently good to provide useful information for numerical weather prediction.

An Initial Evaluation of SSMIS Radiances for Radiance Assimilation Applications

The first Special Sensor Microwave Imager/Sounder (SSMIS) was launched on 18th October 2003 and combines the surface viewing channels of its predecessor (SSMI) with a range of temperature and moisture sounding channels. The accuracy requirements set by numerical weather prediction data assimilation applications for temperature sounding channels are demanding (~0.2 K). The post-launch Cal/Val program highlighted two small, but significant, sources of bias in the SSMIS radiance data associated with solar intrusions into the warm calibration load and with thermal emission from the main reflector. These effects have been studied and initial software mitigation measures are now in place. Data assimilation experiments at the Met Office have shown that the inclusion of SSMIS data reduces short range (day 1-3) forecast errors in southern hemisphere PMSL by 1-3%. Assimilation experiments at ECMWF show that the inclusion of SSMIS radiances from the lower atmospheric temperature sounding channels produces more than half of the impact of NOAA-15 AMSU. Further improvements are expected as the correction algorithms are refined in future

Assessment and Assimilation of FY-3 Humidity Sounders and Imager in the UK Met Office Global Model

China’s FengYun 3 (FY-3) polar orbiting satellites are set to become an important source of observational data for numerical weather prediction (NWP), atmospheric reanalyses, and climate monitoring studies over the next two decades. As part of the Climate Science for Service Partnership China (CSSP China) program, FY-3B Microwave Humidity Sounder 1 (MWHS-1) and FY-3C MWHS-2 observations have been thoroughly assessed and prepared for operational assimilation. This represents the first time observations from China’s polar orbiting satellites have been used in the UK’s global NWP model. Since 2016, continuous data quality monitoring has shown occasional bias changes found to be correlated to changes in the energy supply scheme regulating the platform heating system and other transient anomalies. Nonetheless, MWHS-1 and MWHS-2 significantly contribute to the 24-h forecast error reduction by 0.3% and 0.6%, respectively, and the combination of both instruments is shown to improve the fit to the model background of independent sounders by up to 1%. The observations from the Microwave Radiation Imager (MWRI) also are a potentially significant source of benefits for NWP models, but a solar-dependent bias observed in the instrument half-orbits has prevented their assimilation. This paper presents the bases of a correction scheme developed at the Met Office for the purpose of a future assimilation of MWRI data.摘要中国风云3号极轨卫星在未来二十年将作为重要的观测资料源, 用于数值天气预报、大气再分析产品和气候监测研究. 本项研究作为“面向服务伙伴的气候科学”(CSSP中国)的内容之一, 对风云3B微波探测器1(MWHS-1)和3C微波探测器2(MWHS-2)的观测资料作了系统评估, 同时对其进行了业务数值预报模式的同化分析.本项研究给出了首次用于英国全球数值天气预报模式的中国极轨卫星观测结果. 自2016起, 连续数据质量检验表明上述卫星资料的偶然偏差变化是与影响仪器平台加热系统和其它瞬时异常的能量供给方案有关. 尽管存在这些偏差, MWHS-1和MWHS-2依然可以分别显著地减少24小时预报偏差0.3%和0.6%, 而两个资料结合使用后可使24小时预报偏差减少1%. 微波成像仪观测(MWRI)也是对数值天气预报有重要帮助的资料源, 但该仪器半轨道检测到的与太阳辐射有关的偏差不利于该资料的数据同化应用. 本项研究还介绍了英国气象局开发用于未来MWRI资料同化的订正算法的基本原理.

The Impact of Satellite Derived Land Surface Temperatures on Numerical Weather Prediction Analyses and Forecasts

Land surface temperature (LST) observations from a variety of satellite instruments operating in the infrared have been compared to estimates of surface temperature from the Met Office operational numerical weather prediction (NWP) model. The comparisons show that during the day the NWP model can under predict the surface temperature by up to 10 K in certain regions such as the Sahel and Southern Africa. By contrast at night the differences are generally smaller. Matchups have also been performed between satellite LSTs and observations from an in situ radiometer located in Southern England within a region of mixed land use. These matchups demonstrate good agreement at night and suggest that the satellite uncertainties in LST are less than 2 K. The Met Office surface analysis scheme has been adapted to utilize nighttime LST observations. Experiments using these analyses in an NWP model have shown a benefit to the resulting forecasts of near surface air temperature, particularly over Africa.