An improved HIRS upper tropospheric water vapor dataset and its correlations with major climate indices (original) (raw)
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Journal of Geophysical Research-Atmospheres, 2013
Within the SPARC Data Initiative, the first comprehensive assessment of the quality of 13 water vapor products from 11 limb-viewing satellite instruments (LIMS, SAGE II, UARS-MLS, HALOE, POAM III, SMR, SAGE III, MIPAS, SCIAMACHY, ACE-FTS, and Aura-MLS) obtained within the time period 1978-2010 has been performed. Each instrument's water vapor profile measurements were compiled into monthly zonal mean time series on a common latitude-pressure grid. These time series serve as basis for the "climatological" validation approach used within the project. The evaluations include comparisons of monthly or annual zonal mean cross sections and seasonal cycles in the tropical and extratropical upper troposphere and lower stratosphere averaged over one or more years, comparisons of interannual variability, and a study of the time evolution of physical features in water vapor such as the tropical tape recorder and polar vortex dehydration. Our knowledge of the atmospheric mean state in water vapor is best in the lower and middle stratosphere of the tropics and midlatitudes, with a relative uncertainty of˙2-6% (as quantified by the standard deviation of the instruments' multiannual means). The uncertainty increases toward the polar regions (˙10-15%), the mesosphere (˙15%), and the upper troposphere/lower stratosphere below 100 hPa (˙30-50%), where sampling issues add uncertainty due to large gradients and high natural variability in water vapor. The minimum found in multiannual (1998-2008) mean water vapor in the tropical lower stratosphere is 3.5 ppmv (˙14%), with slightly larger uncertainties for monthly mean values. The frequently used HALOE water vapor data set shows consistently lower values than most other data sets throughout the atmosphere, with increasing deviations from the multi-instrument mean below 100 hPa in both the tropics and extratropics. The knowledge gained from these comparisons and regarding the quality of the individual data sets in different regions of the atmosphere will help to improve model-measurement comparisons (e.g., for diagnostics such as the tropical tape recorder or seasonal cycles), data merging activities, and studies of climate variability.
Technical Note: 30 years of HIRS data of upper tropospheric humidity
Atmospheric Chemistry and Physics, 2014
We use 30 years of intercalibrated HIRS (High-Resolution Infrared Radiation Sounder) data to produce a 30-year data set of upper tropospheric humidity with respect to ice (UTH<sub>i</sub>). Since the required brightness temperatures (channels 12 and 6, <i>T</i><sub>12</sub> and…
Journal of Geophysical Research, 2008
1] We compare matched retrievals of upper tropospheric water vapor (UTWV) mixing ratios from the Microwave Limb Sounder (MLS) instrument on the Aura satellite, and the Atmospheric Infrared Sounder (AIRS) instrument on the Aqua satellite. Because each instrument's sampling is affected by tropical conditions, about half of mutually observed scenes in the tropics yield simultaneous successful retrievals from both systems. The fraction of mutually retrieved scenes drops to 30% at higher latitudes where clouds significantly inhibit AIRS sounding. Essentially all scenes observed by MLS in extratropical and polar regions yield successful retrievals. At 250 hPa in the tropics, measurements from the two instruments are highly correlated, the differences of their means ( D q ) are smaller than 10%, and the standard deviations of their differences (s q ) are 30% or less. At 300 hPa, MLS means are drier by 10-15%, and s q is 40-60%, indicating that responses of MLS and AIRS to UTWV perturbations are not one-to-one. Root mean square agreement is also poorer over the poles at 300 hPa and at 200 and 150 hPa at lower latitudes. In these regions, j D q j = 10% or more, and s q = 40-70%. Correlations between the two data sets are 0.7-0.9 at 300 and 250 hPa globally and at 200 hPa in the tropics. This high correlation indicates that s q of 50% or greater comes mainly from systematic differences in sensitivity of the two instruments, especially for small and large UTWV amounts; larger values of s q are generally not due to large random errors from either instrument. An AIRS low-end sensitivity threshold of 15-20 ppmv leads to poorer agreement under the driest conditions. Disagreement at 300 hPa likely comes from overestimation by MLS for the wettest conditions of >400 ppmv. While MLS is biased slightly dry overall at 300 hPa, it is biased wet in the wettest regions, particularly those associated with deep convection. These sensitivity differences explain nonunity slopes of linear fits to the two data sets. MLS everywhere has a greater dynamic range than AIRS, with larger maxima and smaller minima. Good agreement at 250 hPa suggests AIRS uncertainties of 25% up to the reported 250-200 hPa layer in the tropics and extratropics, consistent with previous comparisons with balloon-and aircraft-borne instruments. The agreement at 250 hPa also indicates that MLS is reliable from its reported 215-hPa level upward in altitude.
Estimating Upper-Tropospheric Water Vapor from SSM/T-2 Satellite Measurements
Journal of Applied Meteorology, 2003
A method and a passive microwave retrieval algorithm have been developed to retrieve upper-tropospheric water vapor (UTW) from Special Sensor Microwave Water Vapor Profiler (SSM/T-2) measurements taken at three discrete frequencies near the 183-GHz water vapor line. The algorithm is based on physical relaxation utilizing statistical covariance information to provide initial-guess profiles and to constrain the updating step in the relaxation process. The scheme incorporates a method to remove SSM/T-2 brightness temperature bias in comparison with collocated simulated brightness temperatures. Correction functions are designed for the three SSM/T-2 183-GHz channels. The algorithm is validated against radiosonde observations and collocated SSM/ T-2 brightness temperatures. Under clear-sky and nonprecipitating-cloud conditions, the UTW retrievals exhibit an rms error of 0.68 kg m Ϫ2 with integrated water vapor biases below 5% for the upper-tropospheric layers of 700-500 and 500-200 hPa. The retrieval provides an independent source of satellite-derived water vapor information in the upper troposphere, distinct from upper-tropospheric humidity information retrieved from thermal infrared (IR) measurements around the 6.3-m water vapor absorption band. The microwave retrievals can then be used to cross-check IR retrievals and/or to augment IR retrievals, dependent upon the problem at hand.
Journal of Atmospheric and Oceanic Technology, 2011
A climatology of the diurnal cycles of HIRS clear-sky brightness temperatures was developed based on measurements over the period 2002–07. This was done by fitting a Fourier series to monthly gridded brightness temperatures of HIRS channels 1–12. The results show a strong land–sea contrast with stronger diurnal cycles over land, and extending from the surface up to HIRS channel 6 or 5, with regional maxima over the subtropics. Over seas, the diurnal cycles are generally small and therefore challenging to detect. A Monte Carlo uncertainty analysis showed that more robust results are reached by aggregating the data zonally before applying the fit. The zonal fits indicate that small diurnal cycles do exist over sea. The results imply that for a long-lived satellite such as NOAA-14, drift in the overpass time can cause a diurnal sampling bias of more than 5 K for channel 8 (surface and lower troposphere).
Trends in Global Cloud Cover in Two Decades of HIRS Observations
Journal of Climate, 2005
The frequency of cloud detection and the frequency with which these clouds are found in the upper troposphere have been extracted from NOAA High Resolution Infrared Radiometer Sounder (HIRS) polar-orbiting satellite data from 1979 to 2001. The HIRS/2 sensor was flown on nine satellites from the Television Infrared Observation Satellite-Next Generation (TIROS-N) through NOAA-14, forming a 22-yr record. Carbon dioxide slicing was used to infer cloud amount and height. Trends in cloud cover and high-cloud frequency were found to be small in these data. High clouds show a small but statistically significant increase in the Tropics and the Northern Hemisphere. The HIRS analysis contrasts with the International Satellite Cloud Climatology Project (ISCCP), which shows a decrease in both total cloud cover and high clouds during most of this period.
IEEE Transactions on Geoscience and Remote Sensing, 2000
In this paper, the overall quality of the water vapor profiles of global operational radiosonde data for the period 2000-2009 is investigated using upper tropospheric humidity (UTH) retrieved from microwave satellite data. Overall, the nighttime radiosonde data showed a dry bias (−5% to −15%) over Europe, Australia, and New Zealand and systematically moist bias (greater than 30%) over China and the former Soviet Union. The nighttime sonde data from the U.S. and Canada showed a bias between −10% and 20%. Most stations indicated a daytime radiation dry bias, except for a few stations from the U.S. and the former Soviet Union. A sensorwise comparison showed a large nighttime wet bias for the Russian (MRZ-3A and MARS) and Chinese GZZ-2 sensors, a relatively small nighttime wet bias for the U.S. Sippican and VIZ-B2 sensors, and a nighttime dry bias for the Chinese GTS1, Vaisala (RS80-A, RS80-H, RS90, RS92K, and RS92-SGP), and the U.S. VIZ-MKII sensors. All sensors had a daytime radiation dry bias, except for the Russian MRZ-3A sensor that had a daytime radiation wet bias that could be because of the daytime radiation bias correction. Because of the large differences between different radiosonde sensors, it is essential for UTH studies to only use the data measured using a single type of sensor at any given station.
Satellite observations of upper tropospheric relative humidity, clouds and wind field divergence
… to atmospheric physics, 1995
This paper presents / an observational study of upper level wind field divergence, upper tropospheric relative humidity (UTH) and high level cloud from satellite. Wind fields are derived from successive half-hourly images of the METEOSAT-4 water vapour (WV: 5.7-7.1 (im) channel. The UTH is inferred from the WV image data with a physical retrieval scheme based on radiative forward calculations. Upper tropospheric cloud amounts are based on the C0 2 -slicing technique applied to bi-spectral radiance observations from the High Resolution Infrared Sounder (HIRS) aboard the NOAA-11 and 12 polar orbiting satellites. The previous UTH retrieval has been simplified such that two radiative forward calculations define a linear relationship between observed WV brightness temperature and the UTH for each retrieval. The new approach is computationally more efficient, however, it retains the important dependency of the UTH on local mean temperature and lapse rate. The WV wind vectors provide a dense spatial coverage of the upper tropospheric flow and, thus, can be used to estimate monthly mean wind fields and associated large-scale divergence. Inferred values of the wind field divergence over a scale of 1500 km are between -5xl0 _6 s _1 and 5xl0~6s _1 which is consistent with other observations. The spatial patterns of monthly means of wind field divergence and UTH closely resemble each other although the quantitative relationship is non-linear. A comparison of the UTH with high-level cloud amounts from the HIRS instrument aboard the NOAA polar orbiting satellites also features a high spatial coherence between both data sets. This suggests that largescale dynamics is the governing factor for both the upper tropospheric relative humidity field and the cloud formation processes associated with the humidity fields. Some implications for largescale models are discussed.
Homogenized water vapor absorption band radiances from international geostationary satellites
Geophysical Research Letters
In the past 20+ years, GEO Imagers with infrared 6.5-μm bands have been observing the Earth's atmosphere, providing useful information of upper tropospheric moisture. Due to the instrumental differences and local viewing angles in GEO satellites, these observations are not consistent for generating climate data records (CDRs). In this study, a methodology has been developed to homogenize the 6.5-μm radiances from the international GEO satellites, to generate a consistent CDR. Validations with Infrared Atmospheric Sounding Interferometer radiances from Metops for 2015-2017 for seven GEO Imager sensors show that the GEO radiances are homogenized well with small standard deviation and biases of the differences (smaller for newer sensors), temporally stable radiometric accuracy, and weak angle dependency (even weaker for sensors with two water vapor bands). The homogenized 20+ years of consistent 6.5-μm radiance CDR can be used to evaluate reanalysis and climate models, especially the diurnal variation of the model simulation.