TIROS Operational Vertical Sounder Research Articles

Sea‐surface emissivity parametrization from microwaves to millimetre waves

In preparation for new observations on board the next generation of the European operational meteorological satellite (EUMETSAT Polar System—Second Generation (EPS‐SG)), a parametrization of the sea‐surface emissivity is proposed from 10–700 GHz: Tool to Estimate Sea‐Surface Emissivity from Microwaves to sub‐Millimeter waves (TESSEM2). It is based on the community model FAST microwave Emissivity Model (FASTEM) at frequencies up to 200 GHz, where FASTEM has been calibrated and validated operationally. It follows a physical emissivity model at higher frequencies. A preliminary evaluation of TESSEM2 has been conducted with success, by comparison with airborne International Sub‐Millimetre Airborne Radiometer (ISMAR) observations from 118–325 GHz, under low wind speed (3–5 m s−1) off the coast of Scotland. TESSEM2 is a fast parametrization that can easily be implemented in a community radiative transfer model. The code is available to the community and will be distributed with the next version of Radiative Transfer for the TIROS Operational Vertical Sounder (RTTOV).

Characterization of Bias of Advanced Himawari Imager Infrared Observations from NWP Background Simulations Using CRTM and RTTOV

AbstractStarting in 2014, the new generation of Japanese geostationary meteorological satellites carries an Advanced Himawari Imager (AHI) to provide the observations of visible, near infrared, and infrared with much improved spatial and temporal resolutions. For applications of the AHI measurements in numerical weather prediction (NWP) data assimilation systems, the biases of the AHI brightness temperatures at channels 7–16 from the model simulations are first characterized and evaluated using both the Community Radiative Transfer Model (CRTM) and the Radiative Transfer for the TIROS Operational Vertical Sounder (RTTOV). It is found that AHI biases under a clear-sky atmosphere are independent of satellite zenith angle except for channel 7. The biases of three water vapor channels increase with scene brightness temperatures and are nearly constant except at high brightness temperatures for the remaining infrared channels. The AHI biases at all the infrared channels are less than 0.6 and 1.2 K over ocean and land, respectively. The differences in biases between RTTOV and CRTM with the land surface emissivity model used in RTTOV are small except for the upper-tropospheric water vapor channels 8 and 9 and the low-tropospheric carbon dioxide channel 16. Since the inputs used for simulations are the same for CRTM and RTTOV, the differential biases at the water vapor channels may be associated with subtle differences in forward models.

Potential of microwave observations for the evaluation of rainfall and convection in a regional climate model in the frame of HyMeX and MED-CORDEX

This study evaluates the potential of spaceborne passive microwave observations for assessing decadal simulations of precipitation from a regional climate model through a model-to-satellite approach. A simulation from the Weather and Research Forecasting (WRF) model is evaluated against 2002-2012 observations from the Advanced Microwave Sounding Unit (AMSU-B) and the Microwave Humidity Sounder (MHS) over the Mediterranean region using the radiative transfer code RTTOV (Ra-diative Transfer for Tiros Operational Vertical Sounder). It is first shown that simulated and observed brightness temperatures are consistently correlated for both water vapour and window channels. Yet, although the average simulated and observed brightness temperatures are similar, the range of brightness temperatures is larger in the observations. The difference is presumably due to the too low content of frozen particles in the simulation. To assess this hypothesis, density and altitude of simulated frozen hydrometeors are compared with observations from an airborne cloud radar. Results show that simulated frozen hydrometeors are found at lower median altitude than observed frozen hy-drometeors, with an average content at least 5 times inferior. Spatial distributions of observed and simulated precipitation match reasonably well. However , when using simulated brightness temperatures to diagnose rainfall, the simulation performs very poorly. These results highlight the need of providing more realistic frozen hydrometeors content , which will increase the interest of using passive microwave observations for the long-term evaluation of regional models. In particular, significant improvements are expected from the archiving of convective fluxes of precipitating hydrometeors in future regional model simulation programs.

Estimation of Rainfall Associated with Typhoons over the Ocean Using TRMM/TMI and Numerical Models

This study quantitatively estimated the precipitation associated with a typhoon in the northwestern Pacific Ocean by using a physical algorithm which included the Weather Research and Forecasting model, Radiative Transfer for TIROS Operational Vertical Sounder model, and data from the Tropical Rainfall Measuring Mission (TRMM)/TRMM Microwave Imager (TMI) and TRMM/Precipitation Radar (PR). First, a prior probability distribution function (PDF) was constructed using over three million rain rate retrievals from the TRMM/PR data for the period 2002–2010 over the northwestern Pacific Ocean. Subsequently, brightness temperatures for 15 typhoons that occurred over the northwestern Pacific Ocean were simulated using a microwave radiative transfer model and a conditional PDF was obtained for these typhoons. The aforementioned physical algorithm involved using a posterior PDF. A posterior PDF was obtained by combining the prior and conditional PDFs. Finally, the rain rate associated with a typhoon was estimated by inputting the observations of the TMI (attenuation indices at 10, 19, 37 GHz) into the posterior PDF (lookup table). Results based on rain rate retrievals indicated that rainband locations with the heaviest rainfall showed qualitatively similar horizontal distributions. The correlation coefficient and root-mean-square error of the rain rate estimation were 0.63 and 4.45 mm·h−1, respectively. Furthermore, the correlation coefficient and root-mean-square error for convective rainfall were 0.78 and 7.25 mm·h−1, respectively, and those for stratiform rainfall were 0.58 and 9.60 mm·h−1, respectively. The main contribution of this study is introducing an approach to quickly and accurately estimate the typhoon precipitation, and remove the need for complex calculations.

두 복사전달모델 RTTOV와 CRTM으로부터 산출된 밝기온도와 관측된 밝기온도의 비교

RTTOV와 CRTM은 복사관측자료에 대한 관측연산자로 수치예보에 활용되고 있는 빠른 속도의 복사전달모델이다. 본 연구에서는 두 모델의 기본구조 및 입력자료를 비교했다. 또한, 다양한 파장대를 가진 AMSU-A 마이크로파 센서에 대해 구름에 대한 정보를 포함할 때와 포함하지 않을 때 두 모델로부터 계산된 밝기온도와 관측된 밝기온도를 해양에 대해 비교했다. AMSU-A의 탐측채널(5-14)에 대해서는 두 모델로부터 계산된 밝기온도 값에 큰 차이가 존재하지 않았으나, 대기의 창 채널 및 지표근처의 탐측채널에서는 RTTOV로부터 계산된 밝기온도 값이 관측과 더 가까워 CRTM에 비해 상대적으로 작은 초기추정오차를 보였다. 한편 UM으로부터 제공된 구름물과 얼음의 정보를 추가적으로 활용하였을 때 두 모델로부터 계산된 밝기온도와 관측된 밝기온도의 차이가 감소함을 확인할 수 있었고, 특히 CRTM의 31.4 GHz와 89 GHz 채널에서 모의된 밝기온도와 관측된 밝기온도의 차이가 크게 감소했다. The radiative transfer for TIROS operational vertical sounder (RTTOV) and the community radiative transfer model (CRTM) are two fast radiative transfer models (RTM) that are used as observation operators in numerical weather prediction (NWP) systems. This study compares the basic structure and input data of the two models. With data from Advanced Microwave Sounding Unit-A (AMSU-A), which has channels of various frequencies, observed brightness temperature (<TEX>$T_B$</TEX>) and simulated <TEX>$T_B$</TEX>s from the two models are compared over the ocean surface in two cases-one where cloud information is included and the other without it. Regarding AMSU-A sounding channels (5-14), the two models produce no large significant differences in their calculated <TEX>$T_B$</TEX>, but RTTOV produces smaller first guess (FG) departures (i.e., better results) in window and near-surface sounding channels than does CRTM. When adding cloud water and ice particles from Unified Model (UM), the <TEX>$T_B$</TEX> bias between observations and simulations are reduced in both models and the bias at 31.4 and 89 GHz is substantially decreased in CRTM compared to those of RTTOV.

Land surface VIS/NIR BRDF atlas for RTTOV‐11: model and validation against SEVIRI land SAF albedo product

This study describes the scientific approach and the validation of the visible and near‐infrared snow‐free land surface Bidirectional Reflectance Distribution Function (BRDF) atlas for Version 11 of the Radiative Transfer for the Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) (RTTOV) Forward Model. The atlas provides a global (at a spatial resolution of 0.1°) and monthly mean land surface BRDF for any instrument containing channels with a central wavelength between 0.4 and 2.5 µm, as well as a quality index of the BRDF. It is based on the reconstructed hyperspectral BRDF from the seven channels of the operational and global Moderate Resolution Imaging Spectroradiometer (MODIS) 16 days BRDF kernel‐driven product MCD43C1: a principal component analysis regression method was applied between the seven channels of the MODIS BRDF products and a set of the US Geological Survey hyperspectral reflectance measurements for soils, rocks, and mixtures of both and vegetation surfaces. The comparison of the RTTOV BRDF atlas against the Spinning Enhanced Visible and Infrared Imager (SEVIRI) surface black‐sky albedo products of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Land Satellite Application Facility on Land Surface Analysis (Land‐SAF) shows good spatial and temporal consistency of the RTTOV BRDF atlas when applied on three SEVIRI visible and near‐infrared channels. The RTTOV narrowband black‐sky albedo is retrieved within ±0.01 in absolute accuracy at 0.6 and 1.6 µm and is overestimated by something between 0.01 and 0.03 at 0.8 µm. The temporal variation of the RTTOV broadband black‐sky albedo is consistent with the EUMETSAT Land‐SAF SEVIRI products but overestimated by somewhere between 0.01 and 0.02 when considering the best quality index of the RTTOV BRDF atlas. Less agreement is found in two cases: (i) for extreme geometrical conditions when the satellite zenith angle is greater than 65° and (ii) for lower quality indices of the RTTOV BRDF atlas.

KIAPS 관측자료 처리시스템에서의 AMSU-A 위성자료 초기 전처리와 편향보정 모듈 개발

As a part of the KIAPS Observation Processing System (KOPS), we have developed the modules of satellite radiance data pre-processing and quality control, which include observation operators to interpolate model state variables into radiances in observation space. AMSU-A (Advanced Microwave Sounding Unit-A) level-1d radiance data have been extracted using the BUFR (Binary Universal Form for the Representation of meteorological data) decoder and a first guess has been calculated with RTTOV (Radiative Transfer for TIROS Operational Vertical Sounder) version 10.2. For initial quality checks, the pixels contaminated by large amounts of cloud liquid water, heavy precipitation, and sea ice have been removed. Channels for assimilation, rejection, or monitoring have been respectively selected for different surface types since the errors from the skin temperature are caused by inaccurate surface emissivity. Correcting the bias caused by errors in the instruments and radiative transfer model is crucial in radiance data pre-processing. We have developed bias correction modules in two steps based on 30-day innovation statistics (observed radiance minus background; O-B). The scan bias correction has been calculated individually for each channel, satellite, and scan position. Then a multiple linear regression of the scan-bias-corrected innovations with several predictors has been employed to correct the airmass bias.

A comparative study of different AIRS products for the detection of near-surface temperature inversion: a case study over New Delhi

Two different products from Atmospheric Infrared Sounder (AIRS) with different number of vertical levels were evaluated for their ability to identify near-surface temperature inversion in a case study over New Delhi during a winter month of November–December 2010, when the city is dominated by morning dense fog due to temperature inversion. The standard product with 28 vertical levels and the support product with 100 vertical levels from AIRS were used to study the early morning temperature profile and to compare it with the temperature profile measured by the radiosonde. It was found that the AIRS support product with more vertical levels includes more information than the AIRS standard product that has only 28 vertical levels. The support product identifies more accurately the inversion depth and strength compared with the standard product. We also compared the radiosonde profiles showing near-surface temperature inversion with the temperature profiles retrieved from Advanced TIROS Operational Vertical Sounder (ATOVS). Comparison with ATOVS shows that the hyperspectral sounder such as AIRS provides more information about the temperature inversion.

The sensitivity of land emissivity estimates from AMSR-E at C and X bands to surface properties

Abstract. Microwave observations at low frequencies exhibit more sensitivity to surface and subsurface properties with little interference from the atmosphere. The objective of this study is to develop a global land emissivity product using passive microwave observations from the Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) and to investigate its sensitivity to land surface properties. The developed product complements existing land emissivity products from SSM/I and AMSU by adding land emissivity estimates at two lower frequencies, 6.9 and 10.65 GHz (C- and X-band, respectively). Observations at these low frequencies penetrate deeper into the soil layer. Ancillary data used in the analysis, such as surface skin temperature and cloud mask, are obtained from International Satellite Cloud Climatology Project (ISCCP). Atmospheric properties are obtained from the TIROS Operational Vertical Sounder (TOVS) observations to determine the small upwelling and downwelling atmospheric emissions as well as the atmospheric transmission. A sensitivity test confirms the small effect of the atmosphere but shows that skin temperature accuracy can significantly affect emissivity estimates. Retrieved emissivities at C- and X-bands and their polarization differences exhibit similar patterns of variation with changes in land cover type, soil moisture, and vegetation density as seen at SSM/I-like frequencies (Ka and Ku bands). The emissivity maps from AMSR-E at these higher frequencies agree reasonably well with the existing SSM/I-based product. The inherent discrepancy introduced by the difference between SSM/I and AMSR-E frequencies, incidence angles, and calibration has been assessed. Significantly greater standard deviation of estimated emissivities compared to SSM/I land emissivity product was found over desert regions. Large differences between emissivity estimates from ascending and descending overpasses were found at lower frequencies due to the inconsistency between thermal IR skin temperatures and passive microwave brightness temperatures which can originate from below the surface. The mismatch between day and night AMSR-E emissivities is greater than ascending and descending differences of SSM/I emissivity. This is because of unique orbit time of AMSR-E (01:30 a.m./p.m. LT) while other microwave sensors have orbit time of 06:00 to 09:00 (a.m./p.m.). This highlights the importance of considering the penetration depth of the microwave signal and diurnal variability of the temperature in emissivity retrieval. The effect of these factors is greater for AMSR-E observations than SSM/I observations, as AMSR-E observations exhibit a greater difference between day and night measures. This issue must be addressed in future studies to improve the accuracy of the emissivity estimates especially at AMSR-E lower frequencies.

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.

Arctic Cloud Changes from Surface and Satellite Observations

Abstract Visual cloud reports from land and ocean regions of the Arctic are analyzed for total cloud cover. Trends and interannual variations in surface cloud data are compared to those obtained from Advanced Very High Resolution Radiometer (AVHRR) and Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) satellite data. Over the Arctic as a whole, trends and interannual variations show little agreement with those from satellite data. The interannual variations from AVHRR are larger in the dark seasons than in the sunlit seasons (6% in winter, 2% in summer); however, in the surface observations, the interannual variations for all seasons are only 1%–2%. A large negative trend for winter found in the AVHRR data is not seen in the surface data. At smaller geographic scales, time series of surface- and satellite-observed cloud cover show some agreement except over sea ice during winter. During the winter months, time series of satellite-observed clouds in numerous grid boxes show variations that are strangely coherent throughout the entire Arctic.

The GCM‐Oriented CALIPSO Cloud Product (CALIPSO‐GOCCP)

This article presents the GCM‐Oriented Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud Product (GOCCP) designed to evaluate the cloudiness simulated by general circulation models (GCMs). For this purpose, Cloud‐Aerosol Lidar with Orthogonal Polarization L1 data are processed following the same steps as in a lidar simulator used to diagnose the model cloud cover that CALIPSO would observe from space if the satellite was flying above an atmosphere similar to that predicted by the GCM. Instantaneous profiles of the lidar scattering ratio (SR) are first computed at the highest horizontal resolution of the data but at the vertical resolution typical of current GCMs, and then cloud diagnostics are inferred from these profiles: vertical distribution of cloud fraction, horizontal distribution of low, middle, high, and total cloud fractions, instantaneous SR profiles, and SR histograms as a function of height. Results are presented for different seasons (January–March 2007–2008 and June–August 2006–2008), and their sensitivity to parameters of the lidar simulator is investigated. It is shown that the choice of the vertical resolution and of the SR threshold value used for cloud detection can modify the cloud fraction by up to 0.20, particularly in the shallow cumulus regions. The tropical marine low‐level cloud fraction is larger during nighttime (by up to 0.15) than during daytime. The histograms of SR characterize the cloud types encountered in different regions. The GOCCP high‐level cloud amount is similar to that from the TIROS Operational Vertical Sounder (TOVS) and the Atmospheric Infrared Sounder (AIRS). The low‐level and middle‐level cloud fractions are larger than those derived from passive remote sensing (International Satellite Cloud Climatology Project, Moderate‐Resolution Imaging Spectroradiometer–Cloud and Earth Radiant Energy System Polarization and Directionality of Earth Reflectances, TOVS Path B, AIRS–Laboratoire de Météorologie Dynamique) because the latter only provide information on the uppermost cloud layer.

Toward a consistent reanalysis of the upper stratosphere based on radiance measurements from SSU and AMSU‐A

AbstractRadiance measurements from the Stratospheric Sounding Unit (SSU) and the Advanced Microwave Sounding Unit (AMSU‐A) are the primary source of information for stratospheric temperature in reanalyses of the satellite era. To improve the time consistency of the reanalyses, radiance biases need to be properly understood and accounted for in the assimilation system. The investigation of intersatellite differences between SSU and AMSU‐A radiance observations shows that these differences are not accurately reproduced by the operational version of the radiative transfer model for the TIROS Operational Vertical Sounder (RTTOV‐8). We found that this deficiency in RTTOV was mainly due to the treatment of the Zeeman effect (splitting of the oxygen absorption lines at 60 GHz) and to changes in the spectral response function of the SSU instrument that are not represented in RTTOV. On this basis we present a revised version of RTTOV that can reproduce SSU and AMSU‐A intersatellite radiance differences more accurately.Assimilation experiments performed with the revised version of RTTOV in a four‐dimensional variational analysis system (4D‐Var) show some improvements in the stratospheric temperature analysis. However, significant jumps in the stratospheric temperature analysis still occur when switching satellites, which is due to the fact that systematic errors in the forecast model are only partially constrained by observations. Using a one‐dimensional retrieval equation, we show that both the extent and vertical structure of the partial bias corrections must inevitably change when the nature of the radiance measurement changes with the transition from SSU to AMSU‐A. Copyright © 2009 Royal Meteorological Society

The Influences of TOVS Radiance Assimilation on Temperature and Moisture Tendencies in JRA-25 and ERA-40

Abstract A Japanese long-term reanalysis (JRA-25) was completed in 2006 utilizing the comprehensive set of observations from the 40-yr ECMWF Re-Analysis (ERA-40). JRA-25 and ERA-40 adopted the same type of assimilation systems: 3DVAR with direct use of satellite sounding radiances. Long-term upper-air thermal tendencies in both reanalyses are examined and compared with the observational deep-layer temperatures of the University of Alabama in Huntsville (UAH) and Remote Sensing Systems (RSS). The upper-air temperature tendencies in the reanalyses are significantly different from those of UAH and RSS, and they appear to be influenced by the way the observations of the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) are used. This study focuses on documenting problems in TOVS assimilation, especially problems in bias corrections used in the reanalyses. Referring to quantitative results in an examination of biases between the reanalyses and raw TOVS observations, this study identifies (i) spurious thermal tendencies derived from transitions in TOVS and in the reanalysis calculation streams, (ii) an excessive enhancement of the tropical water cycle in ERA-40, and (iii) an excessive cooling trend and unstable behavior in the stratospheric temperature in JRA-25. The results of this study suggest that any inconsistencies in TOVS usage can lead to serious inconsistencies in the reanalyses. Therefore, time-consuming efforts to obtain reliable observational information from TOVS are necessary for further progress in reanalyses.

Comparison of High-Cloud Characteristics as Estimated by Selected Spaceborne Observations and Ground-Based Lidar Datasets

Abstract The characterization of high clouds as performed from selected spaceborne observations is assessed in this article by employing a number of worldwide ground-based lidar multiyear datasets as reference. Among the latter, the ground lidar observations conducted at Lannion, Bretagne (48.7°N, 3.5°W), and Palaiseau, near Paris [the Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA) observatory: 48.7°N, 2.2°E], both in France, are discussed in detail. High-cloud altitude statistics at these two sites were found to be similar. Optical thicknesses disagree, and possible reasons were analyzed. Despite the variety of instruments, observation strategies, and methods of analysis employed by different lidar groups, high-cloud optical thicknesses from the Geoscience Laser Altimeter System (GLAS) on board the Ice, Cloud and land Elevation Satellite (ICESat) were found to be consistent on the latitude band 40°–60°N. Respective high-cloud altitudes agree within 1 km with respect to those from ground lidars at Lannion and Palaiseau; such a finding remains to be verified under other synoptic regimes. Mean altitudes of high clouds from Lannion and Palaiseau ground lidars were compared with altitudes of thin cirrus from the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) Path-B 8-yr climatology for a common range of optical thicknesses (0.1–1.4). Over both sites, the annual altitude distribution of thin high clouds from TOVS Path-B is asymmetric, with a peak around 8–9.5 km, whereas the distribution of high clouds retrieved from ground lidars seems symmetric with a peak around 9.5–11.5 km. Additional efforts in standardizing ground lidar observation and processing methods, and in merging high-cloud statistics from complementary measuring platforms, are recommended.

Estimates of Net Atmospheric Moisture Flux Convergence over the Amazon Basin: A Comparison of Reanalysis Products

Abstract Estimates of the net convergence of atmospheric moisture flux over the Amazon Basin, [C], derived using data products from three global reanalyses, the NCEP–NCAR reanalysis (NCEP-1), the NCEP/Department of Energy reanalysis (NCEP-2), and the 40-yr ECMWF Re-Analysis (ERA-40), are compared. Two types of uncertainty in these [C] estimates are distinguished and quantified: “model-associated uncertainty,” which necessarily arises from imperfections in the numerical weather models or data assimilation algorithms, and “postprocessing uncertainty” introduced by operations performed on the original reanalysis data products to compute [C], particularly the finite-difference approximation of divergence. Model-associated uncertainty is found to overwhelm the postprocessing error. A closer look at the time series of this field extending over the period 1980–2001, and their comparison to basin-averaged precipitation and runoff data, reveals the signatures of two potential sources of model-associated errors. 1) ERA-40 estimates of [C] exhibit an artificial shift in 1987, possibly produced by the start of assimilation of Special Sensor Microwave Imager (SSM/I) data. The estimates preceding 1988 are negatively biased relative to the remaining time series, and hence subsequent analysis is limited to the 14-yr period 1988–2001. 2) NCEP-1 and NCEP-2 estimates of [C] show a negative bias over the period 1992–98, which likely originates in biased Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) data assimilated by these reanalyses. A measure of the random error in the [C] time series produced by each reanalysis, computed using river discharge data as reference, indicates that ERA-40 gives the most accurate estimates of net atmospheric moisture flux convergence for the aforementioned 14-yr period.

Relationships between Arctic Sea Ice and Clouds during Autumn

Abstract The connection between sea ice variability and cloud cover over the Arctic seas during autumn is investigated by analyzing the 40-yr ECMWF Re-Analysis (ERA-40) products and the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) Polar Pathfinder satellite datasets. It is found that cloud cover variability near the sea ice margins is strongly linked to sea ice variability. Sea ice retreat is linked to a decrease in low-level cloud amount and a simultaneous increase in midlevel clouds. This pattern is apparent in both data sources. Changes in cloud cover can be explained by changes in the atmospheric temperature structure and an increase in near-surface temperatures resulting from the removal of sea ice. The subsequent decrease in static stability and deepening of the atmospheric boundary layer apparently contribute to the rise in cloud level. The radiative effect of this change is relatively small, as the direct radiative effects of cloud cover changes are compensated for by changes in the temperature and humidity profiles associated with varying ice conditions.

Circumpolar transport of a volcanic cloud from Hekla (Iceland)

Hekla volcano (Iceland) erupted on 17 August 1980 and emplaced a sulfur dioxide (SO2) cloud into the north polar stratosphere at a maximum altitude of ∼15 km. The SO2 is tracked using satellite data from the ultraviolet (UV) Nimbus‐7 Total Ozone Mapping Spectrometer (N7/TOMS) and the infrared (IR) High‐resolution Infrared Radiation Sounder (HIRS/2) on the NOAA TIROS Operational Vertical Sounder (TOVS) platform. The eruption emitted ∼0.5–0.7 Tg of SO2, which later split into three distinct clouds, one of which circled the North Pole at the perimeter of an atypically persistent Arctic cyclone for six days, impacting airspace on three continents. Separate clouds drifted across eastern Russia, Alaska, and Canada. Maximum SO2 columns derived from TOMS and HIRS/2 accurately define the volcanic cloud's path and fit trajectories produced by the NOAA Hybrid Single‐Particle Lagrangian Integrated Trajectory (HYSPLIT) model, providing confidence in the model. When combined with the SO2 measurements, trajectory altitudes derived from HYSPLIT provide robust estimates of the altitudes of the SO2 clouds (8–15 km), which would be elusive using either the satellite data or the trajectory model in isolation. Near‐coincident, spectrally discrete UV and IR retrievals are compared in the volcanic cloud and indicate good agreement between TOMS and HIRS/2 SO2 columns for pixels with similar viewing geometry. Hekla eruptions, which follow a pattern of early explosive venting of volcanic gases with significant stratospheric injection, could play a role in promoting Arctic ozone loss, depending on the phase of the North Atlantic Oscillation during the eruption.

NOAA operational sounding products for advanced TOVS

The National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite Data and Information Service (NESDIS) operates a fleet of civilian, polar‐orbiting, environmental satellites that provide users and researchers with a continuous suite of atmospheric and surface products on a global scale. The first advanced TIROS operational vertical sounder (ATOVS) radiometer configuration, onboard NOAA‐15, was successfully launched into an early evening orbit on 13 May 1998. The ATOVS featured the new 13 channel advanced microwave sounding unit (AMSU) module A1, the 2 channel AMSU‐A2 and 5 channel AMSU‐B radiometers, which replaced the MSU and SSU, along with a similar HIRS and AVHRR instrument payload (Goodrun G., Kidwell, K.B. and Winston, W., 2000, NOAA‐KLM users guide: September 2000 revision, Technical Document, National Oceanic and Atmospheric Administration, National Environmental Satellite Data and Information Service, National Climatic Data Center) that had been operational since 1979. The ATOVS onboard NOAA‐16 was successfully launched into an afternoon orbit on 21 September 2000, followed by NOAA‐17 into a late evening orbit on 24 June 2002, creating the first ever three‐satellite constellation of operational polar satellites (ATOVS). The following report summarizes the online and offline scientific processing systems, respectively, for deriving the NESDIS operational ATOVS sounding products and presents a series of results for the unique three‐operational‐satellite configuration of NOAA‐15, 16 and 17. Results focus on the value of the derived products in the analyses of global and regional scale weather, including direct comparisons against collocated numerical weather prediction (NWP) forecast and radiosonde data. The report is prefaced by a brief history of satellite weather products and concludes with future plans to meet expanding user requirements.

The Impacts of Indirect Soil Moisture Assimilation and Direct Surface Temperature and Humidity Assimilation on a Mesoscale Model Simulation of an Indian Monsoon Depression

This study investigates the impact of the Flux-Adjusting Surface Data Assimilation System (FASDAS) and the four-dimensional data assimilation (FDDA) using analysis nudging on the simulation of a monsoon depression that formed over India during the 1999 Bay of Bengal Monsoon Experiment (BOBMEX) field campaign. FASDAS allows for the indirect assimilation/adjustment of soil moisture and soil temperature together with continuous direct surface data assimilation of surface temperature and surface humidity. Two additional numerical experiments [control (CTRL) and FDDA] were conducted to assess the relative improvements to the simulation by FASDAS. To improve the initial analysis for the FDDA and the surface data assimilation (SDA) runs, the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) simulation utilized the humidity and temperature profiles from the NOAA Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS), surface winds from the Quick Scatterometer (QuikSCAT), and the conventional meteorological upper-air (radiosonde/rawinsonde, pilot balloon) and surface data. The results from the three simulations are compared with each other as well as with NCEP–NCAR reanalysis, the Tropical Rainfall Measuring Mission (TRMM), and the special buoy, ship, and radiosonde observations available during BOBMEX. As compared with the CTRL, the FASDAS and the FDDA runs resulted in (i) a relatively better-developed cyclonic circulation and (ii) a larger spatial area as well as increased rainfall amounts over the coastal regions after landfall. The FASDAS run showed a consistently improved model simulation performance in terms of reduced rms errors of surface humidity and surface temperature as compared with the CTRL and the FDDA runs.