4th workshop on assimilating satellite cloud and precipitation observations for NWP

With the introduction of improved data assimilation methods around the turn of the millenium, direct assimilation of cloud and precipitation observations became more feasible. Since then, ECMWF-JCSDA workshops have been held every 5 years to assess and progress the state of the art. This talk will overview past progress and introduce the current workshop and its key questions. These are: (1)...

In this presentation, we will go over the evolution of the collective capability to observe cloud and precipitation from space-based observing systems, as planned or envisioned by major international space agencies. We will highlight potential gaps if any and assess its compatibility with the evolution of the global NWP requirements. Both research and operational missions will be explored, as...

This presentation intends to cover recent development of all-sky infrared assimilation in the research and operational system. Development on all-sky IR assimilation have been recently significantly progressed although it has not yet been implemented in operational systems. Studies showed the value of frequent measurement of all-sky infrared radiances from new generation geostationary...

Microwave observations are characterized by a very rich information content with respect to water in all its different states, from water vapor to condensed water mass. Various developments in the past decade, including major advances regarding radiative transfer, allowed the assimilation of microwave observations within clouds and precipitation. The international community gained a lot in...

Satellite radiances affected by cloud and precipitation are usually associated with meteorologically important regions. As research development has been intensified in the past decade in major NWP centers on the use of all-sky radiance observations, the assimilation of cloudy radiances from the Advanced Microwave Sounding Unit-A (AMSU-A) for ocean fields of view became operational in the...

Observations in the visible range contain a wealth of information which is in many ways complementary to measurements from thermal infrared and microwave sounders. Radiances or reflectances in the visible can see low clouds and fog as well as small scale clouds and also provide data of cloud characteristics themselves. Therefore these data, represent an important data source for...

Work is under way at the Met Office to develop a new all-sky assimilation scheme for infrared radiances from hyperspectral sounders. The aim is to assimilate IR radiances in the majority of cloudy scenes using the multiple-scattering capabilities available in RTTOV. Using a variable observation error model, it is hoped that this will lead to both a significant increase in the usage of IR...

The NASA Global Modeling and Assimilation Office (GMAO) has been pursuing efforts to utilize all-sky (clear+cloudy+precipitating) MW radiance data and has developed a system to assimilate all-sky GPM Microwave Imager (GMI) radiance data in the Goddard Earth Observing System (GEOS) during the last PMM funding period. The system provides additional constraints on the analysis process near the...

The second generation of the EUMETSAT Polar System (EPS-SG) will include the Micro-Wave Imager (MWI) and the Ice Cloud Imager (ICI) conically-scanning radiometers that will be flown on the Metop-SG B satellites.
MWI will have 18 channels ranging from 18 to 183 GHz. The frequencies at 18.7, 23.8, 31.4 and 89 GHz provide continuity to key microwave imager channels for weather forecasting and...

A reflectivity data assimilation technique has been developed to enhance GPM/DPR assimilation in JMA. The data assimilation method is hybrid-4DVar using flow-dependent background-errors estimated from ensemble perturbations. This 4D-Var includes TL/AD of 3-ice cloud microphysics scheme as a strong constraint. In the TL of cloud microphysics scheme, the perturbations of thermodynamic variables...

Cloud related observations, such as those from microwave radiances, have been at the forefront of recent developments in assimilation, but contain limited information on the vertical structure of clouds. Active observations from profiling instruments such as cloud radar or lidar contain a wealth of information on the structure of clouds and precipitation, providing the much-needed vertical...

The representation of clouds, precipitation and their impacts are fundamental for weather forecasting and climate, yet many regime-dependent systematic errors continue to be present in global atmospheric models. There are a wealth of data from passive and active satellite instruments that can help to identify and understand the causes of these errors. In particular, monitoring and assimilation...

This presentation will discuss the most recent developments of the Thompson-Eidhammer aerosol-aware bulk microphysics parameterization in the Weather Research and Forecasting (WRF) model. Detailed comparisons of many types of observed data have been used to improve the scheme over numerous years including satellite, radar, surface, and aircraft observations. The most recent observational...

The challenges of cloud modeling in large scale models and for climate time scales (sub-seasonal to centuries) will be explored. Key problems related to clouds in longer term climate prediction include extreme precipitation, climate forcing and cloud feedbacks. Satellites provide a wealth of data on clouds that are used for evaluation of models in many different ways. Examples of innovative...

This talk will give an overview of the cloudy and rainy biases our community have to face in order to assimilate all-sky satellite data successfully. Furthermore, we will discuss which different options have been explored or are in the pipeline to treat all-sky biases.
One option would be either to ignore or to screen the data in the presence of model bias. For example, at ECMWF the all-sky...

A lightning parametrization was developed at ECMWF, which became operational in June 2018. It can predict total lightning flash densities (cloud-to-ground plus cloud-to-cloud) both in the deterministic and the ensemble forecasting system. Its tangent-linear and adjoint versions were also developed and have been used over the past two years to investigate the possibility to assimilate lightning...

The Joint Center for Satellite Data Assimilation (JCSDA) Community Radiative Transfer Model (CRTM) is a fast, 1-D radiative transfer model used in numerical weather prediction, calibration / validation, etc. across multiple federal agencies and universities. The key benefit of the CRTM is that it is a satellite simulator, in that it provides a highly accurate representation of satellite...

Nowadays, satellite microwave (MW) observations are gaining weight in weather and climate applications. The upcoming Ice Cloud Imager (ICI) mission covering frequencies between 183 and 670 GHz aims at improving the representation of cloud ice in models. Ultimately, ICI will extend the scope of MW assimilation. In stand-alone retrievals and data assimilation, several simplifications are still...

Cloudy infrared observations are not currently fully exploited in operational NWP models. There are many reasons for this and the one we are interested in is the need to have an accurate and fast radiative transfer model to simulate cloud scattering in infrared. In most NWP centers, cloudy infrared observations are assimilated using the grey-cloud approximation. In this approximation clouds...

Visible satellite images provide high-resolution information on
clouds. However, so far they have not been assimilated directly for
operational purposes, as multiple scattering dominates in the visible
spectral range and makes radiative transfer computations with standard
methods complex and slow. Only recently, sufficiently fast and
accurate forward operators have become available. Here...

The assimilation of all-sky radiance data requires a fast and accurate radiative transfer model capable of simulating the scattering and absorption effects of hydrometeors. In the past decade, complex Discrete Dipole Approximation (DDA) scattering calculations have demonstrated that commonly used simplifications in frozen particle shape (i.e., sphere and spheroids) are insufficient for...

Thanks to their explicit microphysical parameterization, non-hydrostatic Cloud Resolving Models (CRM) allow realistic representations of non linear diabatic processes. Forecast errors of thermodynamical variables and hydrometeors can be computed specifically in cloudy and precipitating conditions by applying e.g geographical masks to ensemble of forecasts obtained with such CRMs and by...

Data assimilation schemes blend observational data, with limited coverage, with a short term forecast to produce an analysis, which is meant to be the best estimate of the atmospheric state. Appropriately specifying error statistics is necessary to obtain an optimal analysis. However, observations often measure a higher resolution state than coarse resolution model grids can describe. Hence,...

The quality of a numerical weather prediction (NWP) system depends on the reliability of its forecasts in both its deterministic and probabilistic configurations. Forecast skill then is affected by the accuracy of the NWP model and its physical parametrizations, as well as by initial condition errors, which include the contributions from observation errors, both random and systematic. It...

In the presence of clouds and precipitation, there is a greater need for information on all state variables in a context where both data assimilation and remote sensing become more complicated, because:

1) Clouds, and to a lesser extent precipitation, shut atmospheric windows at optical (UV to IR) and upper-microwave frequencies while also introducing challenges to observation simulation,...

Roland Potthast, Anne Walter, Andreas Rhodin, Nora Schenk, Liselotte Bach, Takemasa Miyoshi, Shunji Kotsuki, Peter Jan van Leeuwen

We discuss the development of non-linear filtering methods for very high-dimensional systems. In this talk, non-linear filtering is developed in the framework of the convective-scale ensemble data assimilation system ICON-KENDA of DWD with upcoming 2km...

The ability of variational data assimilation to deal with moderate non-linearity and non-Gaussianity is thought to have underpinned recent success in assimilating cloud and precipitation-affected satellite observations using the all-sky approach. A pure ensemble assimilation framework relies on linear and Gaussian assumptions, so its ability to handle all-sky observations is less clear. This...

The present study introduced a non-Gaussian Probability Distribution Function (PDF) and a new displace correction method for precipitation into the dual scale neighboring Ensemble-based Variational assimilation (EnVar) scheme in order to assimilate all-sky Microwave Imager (MWI) brightness temperatures (TBs) into a Cloud-Resolving Model (CRM).

The present study chose the precipitation...

Frozen hydrometeors in tropical cyclones are nonspherical. Moreover, depending on the ambient temperature and ice-supersaturation [1], the vertical inhomogeneity of ice particle habit could exist. Significant efforts have been devoted to studying the nonsphericity effect in microwave radiative transfer [e.g., 2]. However, the vertical inhomogeneity effect has not been addressed so far. In this...

Assimilating all-sky Himawari-8 radiances in the heavy rainfall event on 23 August 2018 in Taiwan

Takumi Honda, Shu-Chih Yang, and Takemasa Miyoshi

In August 2018, a tropical depression stayed near Taiwan and induced heavy precipitation over the southwest region of Taiwan. Detailed evolution of this depression was well captured by the Himawari-8 geostationary satellite of the Japan...

Ensemble data assimilation experiments were used to assess the ability of satellite all-sky infrared brightness temperatures and a nonlinear bias correction (BC) method to improve the accuracy of short-range model forecasts. Infrared brightness temperatures from the SEVIRI sensor that are sensitive to clouds and water vapor in the upper troposphere were assimilated at hourly intervals during a...

Enabled by the new fast and accurate forward operator MFASIS (Scheck et. al, 2016), we work on assimilating solar reflectances measured by the SEVIRI instrument on Meteosat Second Generation in our new convective-scale NWP system ICON-D2-KENDA. We discuss key challenges calling for progress in research areas such as cloud microphysics, data assimilation algorithms to deal with the...

The Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) observed the Earth in lower latitudes between 1997 - 2015. Its conical-scan radiometer has nine channels and measured microwave irradiance between 10 and 89 GHz. These data provide information on atmospheric temperature, humidity, clouds, precipitation, as well as sea surface temperature. Radiance data from other...

Microwave observations are becoming more and more useful for numerical weather prediction ; in particular in an all-sky context which is under development at Météo-France. Indeed those observations can bring highly relevant information content on the vertical distribution of water vapor and hydrometeors. The method under investigation at Meteo-France is called the '1D-Bay+4D-Var' and...

The operational FV3-GFS hybrid data assimilation system assimilates microwave radiances, including those affected by non-precipitating clouds. The cloudy scenes are assumed to be overcast. In recent years efforts have been made to improve the observation operator (CRTM), quality control procedures, and the analysis to make the assimilation of precipitation-affected radiance feasible. ...

Solar photovoltaic power plants and grid operators rely on highly accurate and reliable short-term predictions of solar power and the related prognostic variables such as the surface solar irradiance. These on the other hand strongly depend on the proper forecasting of cloudiness and cloud evolution. Cloud scenarios are best observed by satellites. The use of satellite information in...

Cloud Process Nonlinearity and Model Uncertainty in Data Assimilation and Remote Sensing

Derek J. Posselt and Masashi Minamide

Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA

Assimilation of remote sensing observations of clouds and precipitation is challenging for many reasons, including:

• Nonlinearity in cloud and precipitation processes, and in...

The next generation of European polar-orbiting weather satellites (EPS-SG), due to be launched in the 2020s, will carry the novel Ice Cloud Imager (ICI) which has 13 channels measuring frequencies between 183 and 664GHz that are sensitive to scattering by ice crystals in clouds. As well as providing global estimates of bulk ice mass, these observations also have the potential to be assimilated...

Active microwave sensors are becoming widely used observations within the Numerical Weather Prediction community, either for validating model forecasts or for assimilation purposes. Like for the forward simulation of passive microwave observations, radar data simulations require to make assumptions on the scattering properties of hydrometeors. With the objective of simulating both active and...

During the past five years, the Penn State Center for Advanced Data Assimilation and Predictability Techniques (ADAPT) has been devoted to the development and application of techniques to assimilate all-sky radiance at both infrared (IR) and microwave (MW) bands. For radiance from IR imagers, we have developed the Adaptive Observation Error Inflation (AOEI) error model that is able to provide...

This study aims to improve the precipitation forecasts from numerical weather prediction models through effective assimilation of satellite-observed precipitation data. The assimilation of precipitation data is known to be difficult mainly due to highly non-Gaussian statistics of precipitation-related variables. We have been developing a global atmospheric data assimilation system NICAM-LETKF,...

MFASIS is a novel fast radiative transfer method for the simulation of visible satellite images that is fast enough to cope with the computational constraints of operational data assimilation systems and has therefore recently been implemented into RTTOV v12.2 and v12.3. First evaluation and data assimilation experiments using MFASIS in combination with regional models have demonstrated its...

High spatial and temporal resolution image data of the Earth's environment reflecting cloud, precipitating hydrometeor, aerosol, and lower boundary surface conditions abound. Yet the bulk of the information in such observations isn’t yet exploited for the initialization of Numerical Weather Prediction (NWP) model forecasts. This is because most information contained in the imagery data is...

Cloud and precipitation forecasting is both an essential and challenging task in Numerical Weather Prediction (NWP). In this process, a significant part of the errors can be traced back to imperfect initialization of the models. As regards the 3D fields of rain, cloud water, ice crystals, rain and graupel (hydrometeor content fields), several barriers make their initialization a sensitive...

Precipitation and visibility forecasts are crucial for the US Navy; the assimilation of satellite observations in close proximity to the where relevant weather is occurring or will occur is of great value for tactical guidance and decision aids. Assimilation of all-sky microwave imager and sounder data for both temperature and moisture in cloudy areas is an increasingly important source of...

Cloud and precipitation processes are generally highly nonlinear, resulting in strongly non-Gaussian PDF. Particle filters treat non-Gaussian PDF explicitly and would be potentially effective for data assimilation of cloud and precipitation variables. Penny and Miyoshi (2015) developed a Local Particle Filter (LPF) in a form as the ensemble transform matrix of the Local Ensemble Transform...

Motivated by the use of the GFDL microphysics scheme in the FV3GFS, the all-sky radiance assimilation framework has been expanded to include precipitating hydrometeors. In this upgraded all-sky framework, the five hydrometeors, including cloud liquid water, cloud ice, rain, snow and graupel, are the new control variables, replacing the original cloud water control variable. Radiance...

The GNSS Polarimetric Radio Occultations (GNSS PRO) is a new measurement concept being proved aboard the PAZ satellite, operating since May 2018. The technique is based on the 'traditional' GNSS Radio Occultations (GNSS RO), widely used for atmospheric profiling of thermodynamic parameters and assimilated in operational NWP. Adding polarimetric capabilities to the RO system enables to sense...

At present, there are four kinds of sources of ATOVS AMSU-A data available in CMA, including two kinds of DBNet data (as RARS and EUMETcast) and two kinds of global data (as NESDIS and EUMETSAT). There are some differences on satellite kinds, observation coverages and timeliness among different sources.
Up to 2018 only global data are used in global models in CMA. DBNet data have been used...

Total lightning (inter/intra-cloud + cloud-to-ground) is a proven marker of deep convection. Total lightning activity can be documented from low Earth orbit platforms (e. g. the Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission satellite and the International Space Station) and from ground-based lightning locating systems (LLSs). With the advent of optical imagers on...

At DWD the pilot project SINFONY has been set up in 2017 to develop a seamless ensemble prediction system for convective-scale forecasting with forecast ranges of 6 up to 12 hours, which integrates ensemble nowcasting techniques with ensemble numerical model prediction (NWP) in a more or less seamless way. The focus is on severe summertime convective events with associated hazards such as...

The significant positive impact of assimilating AMSU-A in clear sky at ECMWF has long been challenging to replicate when AMSU-A is instead treated in the all-sky data stream. Through various technical changes in the treatment of all-sky AMSU-A data, it is nearing the point where all-sky AMSU-A can outperform its clear-sky counterpart. In hopes of achieving this, the impacts of changes to data...

We present some highlights from recent updates to the all-sky assimilation at ECMWF.

• Changes to consider interchannel correlation in the error model of microwave imagers. For the all-sky assimilation it has been found that a fully-specified covariance matrix that adapts with the cloud amount was needed for this purpose. We find that the tuning of the eigenvectors and the interplay with...