Comparison of cloud products within IASI footprints for the assimilation of cloudy radiances

This article compares different methods of deriving cloud properties in the footprint of the Infrared Atmospheric Sounding Interferometer (IASI), onboard the European MetOp satellite. Cloud properties produced by ten operational schemes are assessed and an intercomparison of the products for a 12 h global acquisition is presented. Clouds cover a large part of the Earth, contaminating most of the radiance data. The estimation of cloud top height and effective amount within the sounder footprint is an important step towards the direct assimilation of cloud-affected radiances. This study first examines the capability of all the schemes to detect and characterize the clouds for all complex situations and provides some indications of confidence in the data. Then the dataset is restricted to thick overcast single layers and the comparison shows a significant agreement between all the schemes. The impact of the retrieved cloud properties on the residuals between calculated cloudy radiances and observations is estimated in the long-wave part of the spectrum

Recent Advances in Improvement of Forecast Skill and Understanding Climate Processes Using AIRS Version-5 Products

AIRS/AMSU is the state of the art infrared and microwave atmospheric sounding system flying aboard EOS Aqua. These observations, covering the period September 2002 until the present, have been analyzed using the AIRS Science Team Version-5 retrieval algorithm. AIRS is a high spectral resolution infrared grating spectrometer with spect,ral coverage from 650 per centimeter extending to 2660 per centimeter, with low noise and a spectral resolving power of 2400. A brief overview of the AIRS Version-5 retrieval procedure will be presented, including the AIRS channels used in different steps in the retrieval process. Many researchers have used these products to make significant advances in both climate and weather applications. Recent significant results of these experiments will be presented, including results showing that 1) assimilation of AIRS Quality Controlled temperature profiles into a General Circulation Model (GCM) significantly improves the ability to predict storm tracks of intense precipitation events; and 2) anomaly time-series of Outgoing Longwave Radiation (OLR) computed using AIRS sounding products closely match those determined from the CERES instrument, and furthermore explain that the phenomenon that global and especially tropical mean OLR have been decreasing since September 2002 is a result of El Nino/La Nina oscillations during this period

THz spectroscopy of the atmosphere for climatology and meteorology applications

We present a new satellite-based instrument concept that will enable global measurements of atmospheric temperature and humidity profiles with unprecedented resolution and accuracy, compared to currently planned missions. It will also provide global measurements of essential climate variables related to ice clouds that will better constrain global climate models. The instrument is enabled by the use of superconducting detectors coupled to superconducting filterbank spectrometers, operating between 50GHz and 850 GHz. We present the science drivers, the current instrument concept and status, and predicted performance

Assessing the Impact of Pre-gpm Microwave Precipitation Observations in the Goddard WRF Ensemble Data Assimilation System

The forthcoming Global Precipitation Measurement (GPM) Mission will provide next generation precipitation observations from a constellation of satellites. Since precipitation by nature has large variability and low predictability at cloud-resolving scales, the impact of precipitation data on the skills of mesoscale numerical weather prediction (NWP) is largely affected by the characterization of background and observation errors and the representation of nonlinear cloud/precipitation physics in an NWP data assimilation system. We present a data impact study on the assimilation of precipitation-affected microwave (MW) radiances from a pre-GPM satellite constellation using the Goddard WRF Ensemble Data Assimilation System (Goddard WRF-EDAS). A series of assimilation experiments are carried out in a Weather Research Forecast (WRF) model domain of 9 km resolution in western Europe. Sensitivities to observation error specifications, background error covariance estimated from ensemble forecasts with different ensemble sizes, and MW channel selections are examined through single-observation assimilation experiments. An empirical bias correction for precipitation-affected MW radiances is developed based on the statistics of radiance innovations in rainy areas. The data impact is assessed by full data assimilation cycling experiments for a storm event that occurred in France in September 2010. Results show that the assimilation of MW precipitation observations from a satellite constellation mimicking GPM has a positive impact on the accumulated rain forecasts verified with surface radar rain estimates. The case-study on a convective storm also reveals that the accuracy of ensemble-based background error covariance is limited by sampling errors and model errors such as precipitation displacement and unresolved convective scale instability

The role of water vapor in climate. A strategic research plan for the proposed GEWEX water vapor project (GVaP)

The proposed GEWEX Water Vapor Project (GVaP) addresses fundamental deficiencies in the present understanding of moist atmospheric processes and the role of water vapor in the global hydrologic cycle and climate. Inadequate knowledge of the distribution of atmospheric water vapor and its transport is a major impediment to progress in achieving a fuller understanding of various hydrologic processes and a capability for reliable assessment of potential climatic change on global and regional scales. GVap will promote significant improvements in knowledge of atmospheric water vapor and moist processes as well as in present capabilities to model these processes on global and regional scales. GVaP complements a number of ongoing and planned programs focused on various aspects of the hydrologic cycle. The goal of GVaP is to improve understanding of the role of water vapor in meteorological, hydrological, and climatological processes through improved knowledge of water vapor and its variability on all scales. A detailed description of the GVaP is presented

Assimilation des observations satellitaires au-dessus des surfaces continentales

Dans les modèles de prévision numérique du temps, les observations satellitaires sont devenues indispensables pour la production d'une analyse atmosphérique optimale. Or, malgré les performances et la maturité des systèmes d'assimilation actuels, ces observations demeurent fortement sous-exploitées au-dessus des surfaces continentales pour différentes raisons. L'objectif de cette étude est d'améliorer la représentation de la surface (en température et émissivité) afin de mieux assimiler les observations de télédétection dans les modèles. Dans un premier temps, nous avons cherché à vérifier la validité des hypothèses de surface pour le calcul de l'émissivité micro-onde au dessus d'une surface enneigée (région de l'Antarctique). L'effet de plusieurs hypothèses de surface sur les émissivités micro-ondes a été étudié et la qualité des simulations de températures de brillance a été sensiblement améliorée par la prise en compte d'une hypothèse pertinente. Par la suite l'objectif était d'étendre l'assimilation des données infrarouges sensibles aux surfaces continentales qui étaient jusque là rejetées des systèmes d'assimilation. Les recherches récemment effectuées pour l'assimilation des données micro-ondes au-dessus des continents, ont montré qu'un tel objectif est atteignable si la surface est mieux caractérisée. J'ai consacré une bonne partie de ma thèse a évaluer le potentiel d'une estimation de l'émissivité et de la température de surface à partir des données du radiomètre SEVIRI (Spinning Enhanced Visible and Infrared Imager) embarqué sur MSG (METEOSAT SECONDE GENERATION). La forte sensibilité aux nuages et les biais assez marqués de la température de surface analysée dans ALADIN m'ont poussée à préférer l'utilisation de climatologies d'émissivités IR du Land-SAF (EUMET-SAT Land Surface Analysis - Satellite Application Facilities) plutôt que d'estimer directement ces valeurs à partir des observations. J'ai montré qu'en me basant sur cette climatologie, on pouvait restituer des températures de surface à partir du canal IR10.8 de même qualité que celles du Land-SAF et que l'utilisation de cette température de surface comme condition aux limites au modèle de transfert radiatif permet d'obtenir de bien meilleures simulations aux canaux SEVIRI. Enfin, des expériences d'assimilation, au sein de deux modèles à aire limitée, ont été conduites afin d'apprécier, pour la première fois, l'impact de l'assimilation des observations IR sensibles à la surface sur la qualité des analyses et des prévisions. L'impact prépondérant fut observé sur les analyses d'humidité avec une tendance à assécher l'atmosphère en période estivale et à l'humidifier en période hivernale. Ce changement d'humidité a été évalué avec succès près de la surface à l'aide de données GPS indépendantes. L'impact sur les prévisions et sur celles des précipitations en particulier, a été jugé positif principalement sur le sud de l'Europe.In numerical weather prediction models, satellite observations are essential to perform optimal atmospheric analyses. Despite the performance and maturity of current assimilation systems, for different reasons these observations remain highly underutilized over land surfaces. This study aims to improve the description of the surface (temperature and emissivity) to better assimilate remote sensing observations in models. Initially, the validity of surface approximations used to calculate the microwave emissivity over snow surface was evaluated (over the Antarctica region). The impact of several surface approximations for microwave emissivity computation was studied and it was found that the quality of brightness temperature simulations was improved using relevant approximations. Thereafter, the objective was to extend the assimilation of infrared surface-sensitive observations over land which were until now rejected by the assimilation system. Recent researches to assimilate microwave observations over land have shown that this objective can be reached with an adequatly described surface. A large part of my PhD was devoted to the evaluate the potential to retrieve land surface emissivity and land surface temperature from data provided by the SEVIRI radiometer (Spinning Enhanced Visible and Infrared Imager) onboard METEO-SAT SECOND GENERATION. The strong sensitivity to clouds and the large bias found in the land surface temperature computed by the ALADIN meso-scale model encouraged me to use infrared emissivity climatology from the Land-SAF (EUMETSAT Land Surface Analysis - Satellite Application Facilities) rather than direct retrieval from SEVIRI observations. I have shown that, with these climatologies, the land surface temperature could be retrieved at channel IR10.8 with the same quality as the one from the Land-SAF. The use of this temperature as boundary conditions of the radiative transfer model improve the brightness temperature simulations at SEVIRI channels. For the first time, assimilation experiments were conduced within the two limited area models to assess the impact of the assimilation of surface-sensitive infrared observations over the analysis and forecast skills. The predominant impact was observed on the analysis of the moisture with a tendency to dry out the atmosphere in summer and increase moisture in winter. The change in moisture was successfully evaluated near the surface, using independent GPS data. The impact on forecasts, in particular the cumulative precipitation forecasts, was considered to be positive mainly over southern Europe

The Assimilation of Hyperspectral Satellite Radiances in Global Numerical Weather Prediction

Hyperspectral infrared radiance data present opportunities for significant improvements in data assimilation and Numerical Weather Prediction (NWP). The increase in spectral resolution available from the Atmospheric Infrared Sounder (AIRS) sensor, for example, will make it possible to improve the accuracy of temperature and moisture fields. Improved accuracy of the NWP analyses and forecasts should result. In this thesis we incorporate these hyperspectral data, using new assimilation methods, into the National Centers for Environmental Prediction's (NCEP) operational Global Data Assimilation System/Global Forecast System (GDAS/GFS) and investigate their impact on the weather analysis and forecasts. The spatial and spectral resolution of AIRS data used by NWP centers was initially based on theoretical calculations. Synthetic data were used to determine channel selection and spatial density for real time data assimilation. Several problems were previously not fully addressed. These areas include: cloud contamination, surface related issues, dust, and temperature inversions. In this study, several improvements were made to the methods used for assimilation. Spatial resolution was increased to examine every field of view, instead of one in nine or eighteen fields of view. Improved selection criteria were developed to find the best profile for assimilation from a larger sample. New cloud and inversion tests were used to help identify the best profiles to be assimilated in the analysis. The spectral resolution was also increased from 152 to 251 channels. The channels added were mainly near the surface, in the water vapor absorption band, and in the shortwave region. The GFS was run at or near operational resolution and contained all observations available to the operational system. For each experiment the operational version of the GFS was used during that time. The use of full spatial and enhanced spectral resolution data resulted in the first demonstration of significant impact of the AIRS data in both the Northern and Southern Hemisphere. Experiments were performed to show the contribution to the improvements in global weather forecasts from the increase in spatial and spectral resolution. Both spatial and spectral resolution increases were shown to make significant contributions to forecast skill. New methods were also developed to check for clouds, inversions and for estimating surface emissivity. Overall, an improved methodology for assimilating hyperspectral AIRS data was achieved

Assimilation for Skin SST in the NASA GEOS Atmospheric Data Assimilation System

The present article describes the sea surface temperature (SST) developments implemented in the Goddard Earth Observing System, Version 5 (GEOS) Atmospheric Data Assimilation System (ADAS). These are enhancements that contribute to the development of an atmosphere-ocean coupled data assimilation system using GEOS. In the current quasi-operational GEOS-ADAS, the SST is a boundary condition prescribed based on the OSTIA product, therefore SST and skin SST (Ts) are identical. This work modifies the GEOS-ADAS Ts by modelling and assimilating near sea surface sensitive satellite infrared (IR) observations. The atmosphere-ocean interface layer of the GEOS atmospheric general circulation model (AGCM) is updated to include near-surface diurnal warming and cool-skin effects. The GEOS analysis system is also updated to directly assimilate SST-relevant Advanced Very High Resolution Radiometer (AVHRR) radiance observations. Data assimilation experiments designed to evaluate the Ts modification in GEOS-ADAS show improvements in the assimilation of radiance observations that extend beyond the thermal infrared bands of AVHRR. In particular, many channels of hyperspectral sensors, such as those of the Atmospheric Infrared Sounder (AIRS), and Infrared Atmospheric Sounding Interferometer (IASI) are also better assimilated. We also obtained improved fit to withheld insitu buoy measurement of near-surface SST. Evaluation of forecast skill scores show neutral to marginal benefit from the modified Ts

GEWEX water vapor assessment (G-VAP): final report

Este es un informe dentro del Programa para la Investigación del Clima Mundial (World Climate Research Programme, WCRP) cuya misión es facilitar el análisis y la predicción de la variabilidad de la Tierra para proporcionar un valor añadido a la sociedad a nivel práctica. La WCRP tiene varios proyectos centrales, de los cuales el de Intercambio Global de Energía y Agua (Global Energy and Water Exchanges, GEWEX) es uno de ellos. Este proyecto se centra en estudiar el ciclo hidrológico global y regional, así como sus interacciones a través de la radiación y energía y sus implicaciones en el cambio global. Dentro de GEWEX existe el proyecto de Evaluación del Vapor de Agua (VAP, Water Vapour Assessment) que estudia las medidas de concentraciones de vapor de agua en la atmósfera, sus interacciones radiativas y su repercusión en el cambio climático global.El vapor de agua es, de largo, el gas invernadero más importante que reside en la atmósfera. Es, potencialmente, la causa principal de la amplificación del efecto invernadero causado por emisiones de origen humano (principalmente el CO2). Las medidas precisas de su concentración en la atmósfera son determinantes para cuantificar este efecto de retroalimentación positivo al cambio climático. Actualmente, se está lejos de tener medidas de concentraciones de vapor de agua suficientemente precisas para sacar conclusiones significativas de dicho efecto. El informe del WCRP titulado "GEWEX water vapor assessment. Final Report" detalla el estado actual de las medidas de las concentraciones de vapor de agua en la atmósfera. AEMET ha colaborado en la generación de este informe y tiene a unos de sus miembros, Xavier Calbet, como co-autor de este informe