Atmospheric Infrared Sounder Data Research Articles

A Decade of Spaceborne Observations of the Arctic Atmosphere: Novel Insights from NASA’s AIRS Instrument

Abstract Arctic sea ice is declining rapidly and its annual ice extent minima reached record lows twice during the last decade. Large environmental and socioeconomic implications related to sea ice reduction in a warming world necessitate realistic simulations of the Arctic climate system, not least to formulate relevant environmental policies on an international scale. However, despite considerable progress in the last few decades, future climate projections from numerical models still exhibit the largest uncertainties over the polar regions. The lack of sufficient observations of essential climate variables is partly to blame for the poor representation of key atmospheric processes, and their coupling to the surface, in climate models. Observations from the hyperspectral Atmospheric Infrared Sounder (AIRS) instrument on board the National Aeronautics and Space Administration (NASA)’s Aqua satellite are contributing toward improved understanding of the vertical structure of the atmosphere over the poles since 2002, including the lower troposphere. This part of the atmosphere is especially important in the Arctic, as it directly impacts sea ice and its short-term variability. Although in situ measurements provide invaluable ground truth, they are spatially and temporally inhomogeneous and sporadic over the Arctic. A growing number of studies are exploiting AIRS data to investigate the thermodynamic structure of the Arctic atmosphere, with applications ranging from understanding processes to deriving climatologies—all of which are also useful to test and improve parameterizations in climate models. As the AIRS data record now extends more than a decade, a select few of many such noteworthy applications of AIRS data over this challenging and rapidly changing landscape are highlighted here.

Application of Satellite- and NWP-Derived Wind Profiles to Military Airdrop Operations

AbstractThe Joint Precision Airdrop System (JPADS) has revolutionized military high-altitude airdrop capability, allowing delivery of equipment and supplies to smaller drop zones from higher altitudes than was previously possible. This capability relies on accurate wind data, currently provided by GPS dropsondes released in the vicinity of the drop zone shortly before the airdrop. This research investigates the potential for a wind-profiling algorithm to generate the required wind data from passive IR and microwave satellite soundings, eliminating the requirement for a hazardous dropsonde pass near the drop zone. The Atmospheric Infrared Sounder (AIRS) provides a 3D temperature field and determines the heights of 100 standard levels. From these data, the slopes of the isobaric pressure surfaces and temperature gradients are used to calculate wind speed and direction using the thermal wind relationship. The accuracy of these satellite-derived wind profiles is evaluated through comparison with rawinsonde measurements near the coordinates and time of the AIRS sounding. Further investigation of the wind profile accuracy is made by a comparison with numerical weather prediction (NWP) data worldwide, and the effect of cloud cover in the vicinity of the target coordinates is analyzed. The AIRS-derived winds are found to be less accurate than short-term NWP winds for the JPADS application, but the technique developed may be applied to alternate applications, such as use in the stratosphere, where NWP winds are not widely available. The agreement between satellite-retrieved temperatures and measurements at altitudes above 30 km indicates the AIRS data could be used to create accurate, 3D fields of optical turbulence strengths for directed-energy applications.

Stratospheric gravity waves at Southern Hemisphere orographic hotspots: 2003–2014 AIRS/Aqua observations

Abstract. Stratospheric gravity waves from small-scale orographic sources are currently not well-represented in general circulation models. This may be a reason why many simulations have difficulty reproducing the dynamical behavior of the Southern Hemisphere polar vortex in a realistic manner. Here we discuss a 12-year record (2003–2014) of stratospheric gravity wave activity at Southern Hemisphere orographic hotspots as observed by the Atmospheric InfraRed Sounder (AIRS) aboard the National Aeronautics and Space Administration's (NASA) Aqua satellite. We introduce a simple and effective approach, referred to as the “two-box method”, to detect gravity wave activity from infrared nadir sounder measurements and to discriminate between gravity waves from orographic and other sources. From austral mid-fall to mid-spring (April–October) the contributions of orographic sources to the observed gravity wave occurrence frequencies were found to be largest for the Andes (90 %), followed by the Antarctic Peninsula (76 %), Kerguelen Islands (73 %), Tasmania (70 %), New Zealand (67 %), Heard Island (60 %), and other hotspots (24–54 %). Mountain wave activity was found to be closely correlated with peak terrain altitudes, and with zonal winds in the lower troposphere and mid-stratosphere. We propose a simple model to predict the occurrence of mountain wave events in the AIRS observations using zonal wind thresholds at 3 and 750 hPa. The model has significant predictive skill for hotspots where gravity wave activity is primarily due to orographic sources. It typically reproduces seasonal variations of the mountain wave occurrence frequencies at the Antarctic Peninsula and Kerguelen Islands from near zero to over 60 % with mean absolute errors of 4–5 percentage points. The prediction model can be used to disentangle upper level wind effects on observed occurrence frequencies from low-level source and other influences. The data and methods presented here can help to identify interesting case studies in the vast amount of AIRS data, which could then be further explored to study the specific characteristics of stratospheric gravity waves from orographic sources and to support model validation.

Long‐term assessment of Aqua MODIS radiance observation using comparisons with AIRS and IASI

AbstractThis paper presents a detailed comparison between Atmospheric Infrared Sounder (AIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements over the period 2003–2013 and also between MODIS and Infrared Atmospheric Sounding Interferometer (IASI) for the years 2007–2014. For this study AIRS and IASI high spectral resolution data are degraded to MODIS broadband spectral resolution and MODIS fields of view are averaged within the AIRS and IASI footprints. Using spatially uniform scenes, the brightness temperature differences (ΔBT) between MODIS and AIRS are analyzed as a function of scene temperature, scan angle, and solar zenith angle. In general, the measurements of the two sensors are in good agreement (ΔBT less than ±0.2 K) with little or no dependence on the scene temperature. A small dependence is found for the scan angle, where ΔBT varies off nadir up to about ±0.4 K; dependence on the solar zenith angle is also observed, with ΔBT varying up to ±0.5 K. Finally, the variation of ΔBT over time is stable with BT trending less than 0.02 K/yr, with exception of ΔBT for MODIS bands 33 and 35 in the 2011–2013 timeframe. This behavior, which is also identified in MODIS/IASI comparisons, correlates to adjustments in that timeframe of the MODIS nonlinear calibration coefficients.

Anthropogenic emissions and space-borne observations of carbon monoxide over South Asia

The focus of this study is to understand anthropogenic emissions, spatiotemporal variability and trends of carbon monoxide (CO) over South Asia by using datasets from MACCity (Monitoring Atmospheric Composition and Climate, MACC and megaCITY – Zoom for the Environment, CityZEN), REAS (Regional Emission inventory in Asia), AIRS (Atmospheric Infrared Sounder) and SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY). MACCity anthropogenic emissions show an overall increase of 16.5% during 2000–2010. Elevated levels of MACCity CO are found in Indo-Gangetic Basin (IGB), eastern mining region of India, Bangladesh and large urban areas. Some of the major contributors of these emissions have been identified as agricultural waste burning, land transport, industrial production, and energy generation and distribution. An area averaged mean value of AIRS CO at 600hPa is found to be 114±2ppbv (slope −0.48±0.2ppbvyr−1, y-intercept 117±1ppbv and r=0.68) with a minor declining trend at −0.41±0.18%yr−1 over the region during 2003–2015. A strong seasonality in AIRS CO concentration is observed with spring season peak in March 129±1.9ppbv, whereas low values have been observed in summer monsoon with sturdy dip in July 99.6±1.94ppbv. AIRS CO and SCIAMACHY CO Total Column (CO TC) over the study region show spatial patterns similar to MACCity and REAS emissions. An analysis of SCIAMACHY CO TC tendencies has been performed which indicates minor rising trends over some parts of the region. Background CO, Recent Emissions (RE), and spatial anomalies in RE over high anthropogenic activity zones of Indus Basin, Ganges Basin and Eastern Region were analyzed using AIRS and SCIAMACHY CO data.

Analysis of collocated AIRS and MODIS data: a global investigation of correlations between clouds and atmosphere in 2004–2012

ABSTRACTWe used collocated observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) to investigate correlations between cloud parameters and atmospheric stability. We focus on low clouds and specifically investigate the cloud parameters cloud cover and cloud optical thickness from MODIS. The selected atmospheric parameters from AIRS are maximum relative humidity (MRH), lower tropospheric stability (LTS), and water vapour gradient (QTS). The correlations were tested for temporal and regional variation on a global scale and over a time frame of 10 years. Cloud cover and MRH show weak correlations and strong variations on both the temporal and spatial scales. However, cloud cover and lower tropospheric stability show a high correlation in areas with low maritime clouds. The correlation is relatively stable, but slightly increased for the years 2009–2012. Correlations between cloud cover and QTS show a similar behaviour, but slightly stronger variations on the spatial and temporal scales, with better correlations in the East Pacific and from 2004 to 2012. The correlations with cloud optical thickness are weaker in all three cases. A more detailed analysis of the Southeast Pacific shows the influence of El Niño Southern Oscillation (ENSO) on most parameters, but a relatively stable behaviour for the connection of cloud fraction and LTS. Based on the analysis, we suggest that relative humidity is an insufficient approach to link atmospheric properties and low cloud cover. However, we find good correlations with respect to LTS and QTS. LTS in particular indicates low temporal fluctuations, even in the case of influence by ENSO.

An assessment of the consistency between satellite measurements of upper tropospheric water vapor

AbstractWe assess the consistency of the satellite‐based observations of upper tropospheric water vapor (UTWV) by comparing brightness temperature measurements from the channel 12 of High‐Resolution Infrared Radiation Sounder (HIRS), the 183.31 ± 1 GHz channel of Advanced Microwave Sounding Unit‐B (AMSU‐B)/Microwave Humidity Sounder (MHS), and spectral radiances from the Atmospheric Infrared Sounder (AIRS). All three products exhibit consistent spatial and temporal patterns of interannual variability. On decadal time scales, the spatial patterns of trends are similar between all three products; however, the amplitude of the regional trends is noticeably weaker in the HIRS measurements than in either the AMSU‐B/MHS or AIRS data. This presumably reflects the greater clear‐sky sampling limitations of HIRS relative to the other products. However, when averaged over tropical or near‐global spatial scales, the trends between all three products are statistically indistinguishable from each other. The overall consistency between all three products provides important verification of their credibility for documenting long‐term changes in UTWV. A similar analysis is performed for reanalysis‐produced and model‐simulated UTWV using the HIRS record as a benchmark. On decadal time scales, both reanalysis data sets and the multimodel ensemble mean have difficulty in capturing the observed moistening of climatologically dry regions of the subtropics, although the model‐simulated trends are more consistent with the HIRS measurements than the reanalysis data.

한반도 지역에서의 이산화탄소 변화 경향과 AIRS, GOSAT 위성 자료의 정확도 비교

지구 온난화와 기후 시스템에 가장 강력한 영향을 미치는 인자 중 하나인 대기 중 이산화탄소 농도 변화를 지속적으로 모니터링하는 것은 중요하며, 현재 지상 관측과 더불어 위성을 통한 모니터링이 이루어지고 있다. 본 연구에서는 동북아시아 지역 중에서도 1999년부터 주요 대기질 관측소로 운영되어 온 안면도와 고산에서의 대기 중 이산화탄소 농도 변화에 대한 경향성을 전구 월별 평균 값과 비교해 보았으며, 이를 대표적인 온실 기체 관측 위성인 Greenhouse Gases Observing Satellite (GOSAT)과 Atmospheric Infrared Sounder (AIRS)에서 산출되는 값을 안면도와 고산 관측소의 농도 값과 비교하였다. 1999년 1월 대기 중 평균 농도가 371.87 ppm이었던 안면도에서의 이산화탄소 농도는 2013년 12월 405.50 ppm으로 지난 15년간 지속적으로 증가하였다(KMA, 2013). 플라스크 공기 샘플링 방법에 의해 관측된 안면도의 이산화탄소 농도는 같은 기간 전구의 계절 변동성 및 증가 추이가 동일했으나, 동북아시아에서의 이산화탄소 농도의 증가폭이 전구보다 평균 4 ppm 더 높게 나타났다. GOSAT과 AIRS에서 산출된 이산화탄소는 안면도 관측소의 지상 농도와 비교되었으며, 이를 통해 두 위성 자료들의 정확도가 비교하고자 하였다. GOSAT과 AIRS 모두 월별 이산화탄소 농도는 지상 관측소인 안면도의 관측 값보다는 낮은 분포 경향을 보였으나, 계절 변동성과 증가 추이는 동일하게 나타났다. GOSAT과 AIRS에서 산출되는 이산화탄소 농도는 위성별 정확도 분석을 위해 두 위성의 관측 기간 중 동일 관측이 수행된 2011년 1월부터 2012년 12월까지의 자료를 비교하였다. GOSAT은 r이 0.947, RMSD가 5.610, bias가 -5.280으로 r이 0.737, RMSD가 8.574, bias가 -7.316으로 나타난 AIRS보다 동북아시아를 대표하는 안면도 관측소에서의 정확도가 더 높게 나타났다. With the global scale impact of atmospheric <TEX>$CO_2$</TEX> in global warming and climate system, it is necessary to monitor the <TEX>$CO_2$</TEX> concentration continuously on a global scale, where satellite remote sensing has played a significant role recently. In this study, global monthly <TEX>$CO_2$</TEX> concentrations obtained by satellite remote sensing were compared with ground-based measurements at Anmyeon-do and Gosan Korean Global Atmosphere Watch Center. Atmospheric <TEX>$CO_2$</TEX> concentration has increased from 371.87 ppm in January 1999 to 405.50 ppm in December 2013 at Anmyeon-do station (KMA, 2013). Comparison of the continuous measurements by flask air sampling at Anmyeon-do shows the same trend and seasonal variations with those of global monthly mean dataset. Nevertheless, the trends of <TEX>$CO_2$</TEX> over Northeast Asia showed the higher than those of global and the trends also changes with different slope. <TEX>$CO_2$</TEX> products derived from Greenhouse Gases Observing Satellite (GOSAT) and Atmospheric Infrared Sounder (AIRS) were compared with ground-based measurement at Anmyeon-do. The monthly mean values of GOSAT and AIRS data are systemically lower than those obtained at Anmyeon-do, however, the seasonal cycle of satellite products present the similar trend with values of global and Anmyeon-do. The accuracy of <TEX>$CO_2$</TEX> products from GOSAT and AIRS were evaluated statistically for two years from January 2011 to December 2012. GOSAT showed good correlation with the correlation coefficient, RMSD and bias of 0.947, 5.610 and -5.280 to ground-based measurements respectively, while AIRS showed reasonable comparison with 0.737, 8.574 and -7.316 at Anmyeon-do station, respectively.

Quality control of AIRS total column ozone data within tropical cyclones

The Atmospheric Infrared Sounder (AIRS) provides infrared radiance observations twice daily, which can be used to retrieve total column ozone with high spatial resolution. However, it was found that almost all of the ozone data within typhoons and hurricanes were flagged to be of bad quality by the AIRS original quality control (QC) scheme. This determination was based on the ratio of total precipitable water (TPW) error divided by TPW value, where TPW was an AIRS retrieval product. It was found that the difficulty in finding total column ozone data that could pass AIRS QC was related to the low TPWemployed in the AIRS QC algorithm. In this paper, a new two-step QC scheme for AIRS total column ozone is developed. A new ratio is defined which replaces the AIRS TPW with the zonal mean TPW retrieved from the Advanced Microwave Sounding Unit. The first QC step is to remove outliers when the new ratio exceeds 33%. Linear regression models between total column ozone and mean potential vorticity are subsequently developed with daily updates, which are required for future applications of the proposed total ozone QC algorithm to vortex initialization and assimilation of AIRS data. In the second QC step, observations that significantly deviate from the models are further removed using a biweighting algorithm. Numerical results for two typhoon cases and two hurricane cases show that a large amount of good quality AIRS total ozone data is kept within Tropical Cyclones after implementing the proposed QC algorithm.

Increasing evaporation amounts seen in the Arctic between 2003 and 2013 from AIRS data

AbstractThe vertical moisture flux (i.e., evaporation) plays an important role in the Arctic energy budget, the water vapor feedback, and Arctic amplification. It is one of the most uncertain variables, especially in this “new Arctic” climate system, which is dominated by large ice‐free ocean areas for a longer portion of the year. Moisture flux rates, produced using Atmospheric Infrared Sounder (AIRS) data, from the Arctic Ocean and surrounding seas were found to have increased between 2003 and 2013 by 7.2 × 10−4 g m−2 s−1 per year (equivalent to 1.79 W m−2 per year in latent heat). This is a 7% increase in the average moisture flux each year and a 0.12% increase in the yearly global ocean latent heat flux, with some months increasing more than others. The largest increases seen are in the Arctic coastal seas during the spring and fall where there has been a reduction in sea ice cover and an increase in sea surface temperatures. Increases in the moisture flux from the surface also correspond to increases in total atmospheric column water vapor and low‐level clouds, especially in the central Arctic regions. Changes in the atmospheric water vapor in the surrounding seas (e.g., East Greenland) are most likely due to lower latitude transport of moisture rather than from the surface. Yearly, the moisture flux from the surface supplies about 10% of the total column atmosphere water vapor.

Global survey of concentric gravity waves in AIRS images and ECMWF analysis

AbstractConcentric gravity waves (CGWs) are atmospheric phenomena with ring‐shape perturbations originating in the troposphere. They can propagate up to the ionosphere and thermosphere and dynamically couple the lower and upper atmosphere. In this study we developed a novel ring detection algorithm to extract CGWs from the Atmosphere Infrared Sounder (AIRS) radiance data and the European Center for Medium‐Range Weather Forecasting (ECMWF) analysis temperature in the stratosphere to produce the first global maps of such phenomena. The algorithm is capable of estimating wave amplitude, wavelength, propagation direction, and source location. Both AIRS and ECMWF data show a significant diurnal variation in wave propagation direction and generation, in addition to strong seasonal variations in wavelength and amplitude. Occurrence of these ring waves is associated not only with tropical deep convections but also with summertime midlatitude convection, wintertime extratropical jets, and topography such as islands. The high‐resolution ECMWF analysis data capture most of the CGW features, but the wave amplitude is significantly weaker than AIRS observations, showing few convectively generated CGWs.

Validation of AIRS version 6 temperature profiles and surface‐based inversions over Antarctica using Concordiasi dropsonde data

AbstractDuring the 2010 Concordiasi field experiment, 635 dropsondes were released from the lower stratosphere providing in situ atmospheric profiles from the release height (~60 hPa) to the surface over Antarctica. They provide a unique data set of high vertical resolution temperature profiles over the entire Antarctic continent and surrounding ocean. This study uses temperature profiles and derived surface‐based inversion (SBI) properties from the sonde data set to evaluate Atmospheric Infrared Sounder (AIRS) versions 5 (v5) and 6 (v6) temperature profiles. A total of 1486 matched pairs of profiles are available for analysis. The AIRS averaging kernel, representing the AIRS measurement sensitivity, is applied to the dropsonde profiles. The AIRS data are compared to kernel‐averaged dropsonde profiles and found, on average, to have a small cold bias (~0.5°C) (for v6) in the troposphere. AIRS v6 is improved over v5 with both profile‐averaged bias and root‐mean‐square errors reduced by over 25%. Compared to the kernel‐averaged dropsonde profiles, AIRS v6 accurately detects the existence of SBIs in 79% of the profiles and agrees on the inversion depth 79% of the time. AIRS correctly identifies SBIs in 59% of cases when compared to the full‐resolution sonde. AIRS systematically underestimates the SBI intensity. This is due to warmer reported AIRS surface air temperatures (Ta) than Ta measured with the dropsonde. Replacement of AIRS Ta with that measured by the dropsonde improves the agreement in both SBI detection and intensity. If AIRS Ta could be improved, AIRS has the potential to be a stand‐alone SBI detection tool over Antarctica.

Verification of air/surface humidity differences from AIRS and ERA‐Interim in support of turbulent flux estimation in the Arctic

AbstractEvaporation from the Arctic Ocean and its marginal seas is essential for air moisture, cloudiness, and precipitation, as well as for the associated feedbacks, which contribute to the Arctic amplification of climate warming. However, evaporation in the Arctic is still associated with large uncertainties. The Boisvert et al. (2013) moisture flux scheme (BMF13) is based on application of the Atmospheric Infrared Sounder (AIRS) data, which produces high‐quality, global, daily atmospheric temperature and moisture profiles even in the presence of clouds. Comparing the results of BMF13 against the ERA‐Interim reanalysis, we found differences up to 55 W m−2 in the surface latent heat flux in the Beaufort‐East Siberian Seas (BESS). We found out that the quality of the input data for the BMF13 and ERA‐Interim flux schemes was the main cause for the differences. Differences in the input data sets cause moisture flux estimates to differ up to 1.6 × 10−2 g m−2 s−1 (40 W m−2 latent heat flux) in the BESS region, when both data sets were applied to the BMF13 scheme. Thus, the input data sets, AIRS version 6 and ERA‐Interim reanalysis, were compared with a variety of in situ data. In skin temperature ERA‐Interim had twice as large an error as AIRS version 6, but smaller errors in air specific humidity. The results suggested that AIRS data and the BMF13 scheme are a good option to estimate the moisture flux in the Arctic. However, the differences detected demonstrate a need for more in situ measurements of air temperature and humidity in the Arctic.

Retrieval of nitrous oxide from Atmospheric Infrared Sounder: Characterization and validation

AbstractThis paper presents the retrieval algorithm of nitrous oxide (N2O) using the Atmospheric Infrared Sounder (AIRS) on EOS/Aqua, its validation using aircraft measurements, and one possible application for monitoring the global N2O annual trend from 2003 to 2013. The results demonstrate that AIRS is sensitive to N2O in the middle to upper troposphere, with the peak vertical sensitivity between 200 and 750 hPa and the sensitivity in the tropics larger than in the high‐latitude regions. The degrees of freedom of the N2O retrieval are mostly between 1.0 and 1.5. Validation using the aircraft measurement profiles by the High‐Performance Instrumented Airborne Platform for Environmental Research Pole‐to‐Pole Observations program over the Pacific Ocean indicated that the retrieval RMS error is mostly less than 8 ppb (or ~2.1%). One important feature is that the variability of N2O from AIRS is more than 2 times than that of the aircraft measurements in the lower troposphere. In agreement with surface measurements, a nearly linear trend of N2O can be obtained based on limited AIRS data of 1 day in 15 May in each year from 2003 to 2013, and the increase rate of N2O is about 0.72 ppb yr−1. This algorithm will be implemented in AIRS operational retrieval system, enabling the derivation of the N2O for over 20 years using the AIRS, the Infrared Atmospheric Sounding Interferometer, and the Cross‐track Infrared Sounder. Such a unique product will be complementary to currently sparse ground‐based observations for monitoring the N2O trend associated with climate change.

Assessing the performance of GPS radio occultation measurements in retrieving tropospheric humidity in cloudiness: A comparison study with radiosondes, ERA-Interim, and AIRS data sets

We assess the impact that the Global Positioning System radio occultations (GPSRO) measurements have on complementing different data sets in characterizing the lower-to-middle tropospheric humidity in cloudy conditions over both land and oceans using data from 1 August 2006 to 31 October 2006. We use observations from rawinsondes, Global Positioning System radio occultations (GPSRO), Atmospheric Infrared Sounder (AIRS), and the European Center for Medium-Range Weather Forecasts Reanalysis Interim (ERA-Interim). During the selected time period, Constellation Observing System for Meteorology, Ionosphere, and Climate data were not assimilated in ERA-Interim. From each data set, we estimate a zonally averaged tropospheric specific humidity profile at tropical, middle, and high latitudes. Over land, we use rawinsondes as the ground truth and quantify the specific humidity differences and root-mean-square-errors (RMSEs) of the GPSRO, AIRS, and ERA-Interim profiles. GPSRO are beneficial in retrieving lower tropospheric humidity than upper tropospheric profiles, due to their loss of sensitivity at high altitudes. Blending GPSRO with ERA-Interim produces profiles with smaller humidity biases outside the tropics, but GPSRO data do not improve the humidity RMSE when compared to rawinsondes. Combining GPSRO with AIRS leads to smaller humidity bias at the tropics and high latitudes, while reducing humidity's RMSEs. Over oceans, no rawinsonde information is available, and we use ERA-Interim as a reference. Combining GPSRO with AIRS leads to smaller humidity RMSEs than AIRS. We conclude that cross-comparisons and synergies among multi-instrument observations are promising in advancing our knowledge of the tropospheric humidity in cloudy conditions. GPSRO data can contribute to improving humidity retrievals over cloud-covered regions, especially over land and within the boundary layer.

Assimilation of clear sky Atmospheric Infrared Sounder radiances in short-term regional forecasts using community models

Regional assimilation experiments of clear-sky Atmospheric Infrared Sounder (AIRS) radiances were performed using the gridpoint statistical interpolation three-dimensional variational assimilation system coupled to the weather research and forecasting model. The data assimilation system and forecast model used in this study are separate community models; it cannot be assumed that the coupled systems work optimally. Tuning was performed on the data assimilation system and forecast model. Components tuned included the background error covariance matrix, the satellite radiance bias correction, the quality control procedures for AIRS radiances, the forecast model resolution, and the infrared channel selection. Assimilation metrics and diagnostics from the assimilation system were used to identify problems when combining separate systems. Forecasts initiated from analyses after assimilation were verified with model analyses, rawinsondes, nonassimilated satellite radiances, and 24 h–accumulated precipitation. Assimilation of clear sky AIRS radiances showed the largest improvement in temperature and radiance brightness temperature bias when compared with rawinsondes and satellite observations, respectively. Precipitation skill scores displayed minor changes with AIRS radiance assimilation. The 00 and 12 coordinated universal time (UTC) forecasts were typically of better quality than the 06 and 18 UTC forecasts, possibly due to the amount of AIRS data available for each assimilation cycle.

Upper tropospheric water vapour variability over tropical latitudes observed using radiosonde and satellite measurements

The present study deals with using long-term database for upper tropospheric water vapour (UTWV) variability studies over three tropical stations (Gadanki, Singapore and Truk), where different climatic conditions prevail. Over Gadanki (13.5°N, 79.2°E) strong seasonal variation in UTWV is revealed but not over Singapore (1.37°N, 103.98°E) and Truk (7.46°N, 151.85°E) except at 100 hPa. It is examined whether high resolution radiosonde measurements represent well the UTWV by comparing with different satellite based (Atmospheric Infrared Sounder (AIRS), Advanced Microwave Sounding Unit-B (AMSU-B) and Microwave Limb Sounder (MLS)) water vapour measurements. Very good comparison in the nature of variations of UTWV is observed between radiosonde data and satellite data, except over Singapore particularly with AIRS and MLS data, on long-term basis. An attempt is also made to examine the source for UTWV. A close relationship is found between UTWV and deep convection over Gadanki indicating that the source for UTWV is convection particularly during the summer monsoon season.

Frequency of deep convective clouds in the tropical zone from 10 years of AIRS data

Abstract. Deep convective clouds (DCCs) have been widely studied because of their association with heavy precipitation and severe weather events. Changes in the properties of DCCs are likely in a changing climate. Ten years of data collected by Atmospheric Infrared Sounder (AIRS) allow us to identify decadal trends in frequency of occurrence of DCCs over land and ocean. In the past, DCCs have been identified in the thermal infrared by three methods: (1) thresholds based on the absolute value of an atmospheric window channel brightness temperature; (2) thresholds based on the difference between the brightness temperature in an atmospheric window channel and the brightness temperature centered on a strong water vapor absorption line; and (3) a threshold using the difference between the window channel brightness temperature and the tropopause temperature based on climatology. Simultaneous observations of these infrared identified DCCs with the Advanced Microwave Sounding Unit–Humidity Sounder for Brazil (AMSU-HSB) using 183 GHz water channels provide a statistical correlation with microwave deep convection and overshooting convection. In the past 10 years, the frequency of occurrence of DCCs has decreased for the tropical ocean, while it has increased for tropical land. The area of the tropical zone associated with DCCs is typically much less than 1%. We find that the least frequent, more extreme DCCs show the largest trend in frequency of occurrence, increasing over land and decreasing over ocean. The trends for land and ocean closely balance, such that the DCC frequency changed at an insignificant rate for the entire tropical zone. This pattern of essentially zero trend for the tropical zone, but opposite land/ocean trends, is consistent with measurements of global precipitation. The changes in frequency of occurrence of the DCCs are correlated with the Niño34 index, which defines the sea surface temperature (SST) anomaly in the east-central Pacific. This is also consistent with patterns seen in global precipitation. This suggests that the observed changes in the frequency are part of a decadal variability characterized by shifts in the main tropical circulation patterns, which does not fully balance in the 10-year AIRS data record. The regional correlations and anti-correlations of the DCC frequency anomaly with the Multivariate ENSO Index (MEI) provide a new perspective for the regional analysis of past events, since the SST anomaly in the Nino34 region is available in the form of the extended MEI from 1871.

Seasonal cycle of orographic gravity wave occurrence above small islands in the Southern Hemisphere: Implications for effects on the general circulation

Orographic gravity waves generated by flow over the topography of small islands in the southern oceans have been observed from orbit with the Atmospheric Infrared Sounder on the Aqua satellite. We examine the occurrence frequencies of these waves in the stratosphere at ∼40km above 14 islands and examine geographical and seasonal changes. Our results show that these small island mountain waves occur commonly in the stratosphere in the May–September season, though not every day. Differing seasonal variations are evident at different islands, and the seasonal variations are closely related to latitude and prevailing wind patterns. We also examine interannual variability in 2years of data and the relationships between occurrence frequencies, momentum fluxes, and stratospheric and surface winds. The results suggest that stratospheric winds have a first‐order limiting effect on the observations of these island mountain waves in Atmospheric Infrared Sounder (AIRS) data. Surface wind direction and island orographic relief have an additional but secondary influence on the island mountain wave occurrence frequencies in AIRS data. The implications are that these wave events are extremely common and that on many days when the waves are not observed in AIRS data they have likely dissipated and induced a drag force on the atmosphere below the 40km observation level. Observations of momentum flux during these wave events also permit a first estimate of their importance to the general circulation of the Southern Hemisphere.

Cloud-State-Dependent Sampling in AIRS Observations Based on CloudSat Cloud Classification

AbstractThe precision, accuracy, and potential sampling biases of temperature T and water vapor q vertical profiles obtained by satellite infrared sounding instruments are highly cloud-state dependent and poorly quantified. The authors describe progress toward a comprehensive T and q climatology derived from the Atmospheric Infrared Sounder (AIRS) suite that is a function of cloud state based on collocated CloudSat observations. The AIRS sampling rates, biases, and center root-mean-square differences (CRMSD) are determined through comparisons of pixel-scale collocated ECMWF model analysis data. The results show that AIRS provides a realistic representation of most meteorological regimes in most geographical regions, including those dominated by high thin cirrus and shallow boundary layer clouds. The mean AIRS observational biases relative to the ECMWF analysis between the surface and 200 hPa are within ±1 K in T and from −1 to +0.5 g kg−1 in q. Biases because of cloud-state-dependent sampling dominate the total biases in the AIRS data and are largest in the presence of deep convective (DC) and nimbostratus (Ns) clouds. Systematic cold and dry biases are found throughout the free troposphere for DC and Ns. Somewhat larger biases are found over land and in the midlatitudes than over the oceans and in the tropics, respectively. Tropical and oceanic regions generally have a smaller CRMSD than the midlatitudes and over land, suggesting agreement of T and q variability between AIRS and ECMWF in these regions. The magnitude of CRMSD is also strongly dependent on cloud type.