Stephen J. English

Fast generic millimeter-wave emissivity model

In recent year san increasingly diverse range of passive microwave satellite data has become available for applications in numerical weather forecasting, climate studies and environmental monitoring. Top of atmosphere radiance is measured, which as originated from both the surface and the atmosphere. When retrieving atmospheric quantities such as temperature, humidity or cloud liquid water content near the surface it is necessary to account correctly for the contribution to the measured radiance from the surface. This depends on the surface emissivity, which varies widely with surface type, roughness and temperature. For real time applications such as numerical weather forecasting, it is necessary to be able to model the surface emissivity very quickly. There is therefore a need for a fast surface emissivity model has therefore been developed. This is a semi-empirical mode. Some aspects are physically based, for example many surface scan be assumed to be di- electric media. Other aspects such as geometric roughness have been parameterized for speed. For some complex or poorly understood aspects of the electromagnetic interaction empirical adjustments are made to fit observed values. The model has been compared with emissivities derived from aircraft radiometer measurements at 24, 50, 89 and 157 GHz. It is also intended to compare with data from the special sensor microwave imager and advanced microwave sounding unit instruments. For the ocean surface the fast model fits estimated emissivities from airborne radiometers two within 1-2 percent, and it fits the unparameterized model to within 0.1-3 percent.

Airborne retrievals of snow and ice surface emissivity at millimeter wavelengths

Passive microwave radiometers (24-157 GHz) have been flown over Baltic Sea ice and snow sites in April 1995 and on March 15, 1997. Data from these instruments are analyzed with reference to ground measurements of snow and ice conditions, and emissivity spectra are presented for 12 classifications of surface type. A simple model based on dielectric permittivity can accurately represent the microwave spectra of sea ice, but cannot be extended to the behavior of dry snow above 100 GHz without the addition of an extra term to represent volume scattering. The parameterization presented is intended to provide a background for temperature and humidity retrievals from satellite sounders, but the results will be of interest to the snow and ice remote-sensing communities.

An Improved Fast Microwave Water Emissivity Model

Satellite measurements from microwave instruments have made a significant contribution to the skill of numerical weather forecasting, on both global and regional scales. A FAST microwave Emissivity Model (FASTEM), which was developed by the Met Office, U.K., has been widely utilized to compute the surface emitted radiation in forward calculations. However, the FASTEM model was developed for frequencies in the range of 20-60 GHz, and it is biased at higher and lower frequencies. Several critical components such as variable sea surface salinity and full Stokes vector have not been generally taken into account. In this paper, the effects of the permittivity models are investigated, and a new permittivity model is generated by using the measurements for fresh and salt water at frequencies between 1.4 and 410 GHz. A modified sea surface roughness model from Durden and Vesecky is applied to the detailed two-scale surface emissivity calculations. This ocean emissivity model at microwave is now being used in the Community Radiative Transfer Model, and it has resulted in some major improvements in microwave radiance simulations. This paper is a joint effort of the Met Office, U.K., and the Joint Center for the Satellite Data Assimilation, U.S. The model is called as FASTEM-4 in the Radiative Transfer for TIROS Operational Vertical Sounder model.

The Importance of Accurate Skin Temperature in Assimilating Radiances From Satellite Sounding Instruments

An error analysis has been performed, which shows that skin temperature errors are important for sounding channels. An approach for estimating skin temperature and emissivity errors from the dependence of differences between observed and calculated radiances on surface-to-space transmittance is described. Estimates of emissivity and skin temperature error for the operational Met Office data assimilation system are presented as an example, and the implications are discussed, in terms of use of data over different surfaces and in different conditions (e.g., day/night). The results highlight the need for a better emissivity estimate over sea ice than that used at the Met Office and the inaccuracy of the land surface skin temperature that was derived from radiative flux balance at the surface.

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.

Scaling of GNSS Radio Occultation Impact with Observation Number Using an Ensemble of Data Assimilations

AbstractAn ensemble of data assimilations (EDA) approach is used to estimate how the impact of Global Navigation Satellite System (GNSS) radio occultation (RO) measurements scales as a function of observation number in the ECMWF numerical weather prediction system. The EDA provides an estimate of the theoretical analysis and short-range forecast error statistics, based on the ensemble “spread,” which is the standard deviation of the ensemble members about the ensemble mean. This study is based on computing how the ensemble spread of various parameters changes as a function of the number of simulated GNSS RO observations. The impact from 2000 up to 128 000 globally distributed simulated GNSS RO profiles per day is investigated. It is shown that 2000 simulated GNSS RO measurements have an impact similar to real measurements in the EDA and that the EDA-based impact of real data can be related to the impact in observing system experiments. The dependence of the ensemble statistics on observation error statist...

Assessment of FY-3A and FY-3B MWHS Observations

AbstractThe Fengyun-3 series of satellites (FY-3) began in May 2008 with the launch of FY-3A. The onboard Microwave Humidity Sounders (MWHSs) provide vertical information about water vapor, which is important for numerical weather prediction (NWP). The noise equivalent delta temperature (NEDT) of the MWHS is higher than that of the Microwave Humidity Sounder (MHS) instrument (e.g., on board MetOp-B) but lower than that of the older AMSU-B instruments (on board NOAA-15, NOAA-16, and NOAA-17). Assimilation of MWHS observations into the ECMWF Integrated Forecast System (IFS) improved the fit of short-range forecasts to other observations, notably MHS, and also slightly improved the longer-range forecast scores verified against analyses. Also, assimilating the MWHS on board both FY-3A and FY-3B gave a larger impact than either instrument alone. Furthermore, when MWHS and MHS were added separately to a baseline using neither, the impact of MWHS was found to be comparable to that of MHS. Consequently, ECMWF has...

AMSU-B: a new tool for atmospheric research

The U.K. Meteorological Office (UKMO) is providing to NOAA three flight models of the high frequency part of the Advanced Microwave Sounding Unit known as AMSU-B. The AMSU-B is a five channel microwave radiometer with channels centered at 89, 150, 183+/- 1, 183+/- 3 and 183+/- 7 GHz with a field of view of nominally 1.1 degree(s) (i.e. 15 km footprint at nadir). AMSU-B will fly on the NOAA KLM polar orbiters due to be launched in the next few years. All three AMSU-B flight models have undergone a comprehensive test and characterization program to measure the antenna pattern and spectral, radiometric and thermal properties of each instrument. The results from this test program have allowed a procedure for the in-orbit calibration of AMSU-B to be defined. In parallel with the development of the AMSU-B radiometer a program of aircraft radiometer measurements and model development has been carried out with the aim of improving our capability of predicting the radiative transfer through the atmosphere at AMSU-B frequencies. The aircraft radiometer has channels at 89 GHz and 157 GHz which are close to the corresponding window channels of AMSU-B and it can view both upwards and downwards. Measurements of clear transmission, sea surface emissivity and transmission through cloud liquid water have all been analyzed. Based on these measurements a forward radiative transfer model is being developed which will be used in the retrieval of temperature, humidity and cloud liquid water from AMSU.

The Radiometric Sensitivity Requirements for Satellite Microwave Temperature Sounding Instruments for Numerical Weather Prediction

Abstract The sensitivity of NWP forecast accuracy with respect to the radiometric performance of microwave sounders is assessed through a series of observing system experiments at the Met Office and ECMWF. The observing system experiments compare the impact of normal data from a single Advanced Microwave Sounding Unit (AMSU) with that from an AMSU where synthetic noise has been added. The results show a measurable reduction in forecast improvement in the Southern Hemisphere, with improvements reduced by 11% for relatively small increases in radiometric noise [noise-equivalent brightness temperature (NEΔT) increased from 0.1 to 0.2 K for remapped data]. The impact of microwave sounding data is shown to be significantly less than was the case prior to the use of advanced infrared sounder data [Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI)], with microwave sounding data now reducing Southern Hemisphere forecast errors by approximately 10% compared to 40% in the p...

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.