Atmospheric parameters in a subtropical cloud regime transition derived by AIRS and MODIS: observed statistical variability compared to ERA-Interim

Schreier, M. M.; Kahn, Brian H.; Sušelj, K.; Karlsson, Johannes; Ou, S. C.; Yue, Qing; Nasiri, Shaima L.

doi:10.5194/acp-14-3573-2014

Cited by 14 publications

(14 citation statements)

References 66 publications

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“…507 In all climate zones the UCAR-RO, together with the AIRS data set, systematically show 508 drier air in the lower troposphere than all other data sets. Aside from the AIRS low-cloud 509 contamination [Schreier et al, 2014], this behavior could indicate that both AIRS and UCAR-510 RO data sets may not be sensitive enough to properly capture high-moisture air rising from the 511 boundary layer beneath, either due to entrainment and/or convective limitations. This study 512 exploits the short-term RO SH data record in an attempt to quantify differences between the RO 513 time series and other data sets.…”

Section: Figure 7 Same As Figure 3 But the Results Reflect Sh Trendmentioning

confidence: 99%

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Comparisons of the tropospheric specific humidity from GPS radio occultations with ERA–Interim, NASA MERRA and AIRS data

Vergados¹,

Mannucci²,

Ao³

et al. 2017

Preprint

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Abstract. We construct a 9–year data record (2007–2015) of the tropospheric specific humidity (SH) using Global Positioning System radio occultation (GPS RO) observations from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission. This record covers the ±40° latitude belt and includes estimates of the zonally averaged monthly mean SH from 700 hPa up to 400 hPa. It includes three major climate zones: a) the deep tropics (±15°), b) the trade winds belts (±15–30°), and c) the subtropics (±30–40°). Our objective is to compare the RO observations with the European Center for Medium-range Weather Forecasts Re-Analysis Interim (ERA-Interim), the Modern-Era Retrospective analysis for Research and Applications (MERRA), and the Atmospheric Infrared Sounder (AIRS) to examine the consistency among the data sets. We present RO SHs from both JPL and UCAR processing centers to provide an estimate of the structural uncertainty of the RO SH products. The results show that the RO observations capture the seasonal and interannual SH variability as all other data sets. On average, the JPL-RO SH agrees with both reanalyses to within 10 %, is overall larger than all data sets, having maximum differences with AIRS by ~ 10–30 %, and is almost twice as wet as all other data sets in the middle-to-upper troposphere at the subtropics. The UCAR-RO SH also agrees with both reanalyses and AIRS, but is systematically drier than all other data sets. Provided the estimated differences between the RO observations and the rest of the data sets, together with the retrieval uncertainty of the SH products from all data sets, we conclude that RO observations are a valuable independent observing system, which could augment independent reanalyses and satellite platforms. We anticipate that the COSMIC-2 mission will increase the observational sampling; thus, improving the coverage and quality of the observed SH climatology.

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Section: Figure 7 Same As Figure 3 But the Results Reflect Sh Trendmentioning

confidence: 99%

“…The use of IR 62 observations in the lower troposphere still remains a challenge, due to the decreasing information 63 content and the difficulty detecting low-cloud contamination [Schreier et al, 2014] …”

Section: That Induces Errors In 58mentioning

confidence: 99%

Comparisons of the tropospheric specific humidity from GPS radio occultations with ERA–Interim, NASA MERRA and AIRS data

Vergados¹,

Mannucci²,

Ao³

et al. 2017

Preprint

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“…There are few other studies directly evaluating the cloud properties as observations of clouds have their own large uncertainties. However, Schreier et al (2014) and Ahlgrimm and Köhler (2010) have studied trade cumulus clouds represented in ERA-Interim. These are not directly related to deep convective clouds but at least can hint at some of the differences between the reanalysis and observations.…”

Section: Ecmwf Era-interimmentioning

confidence: 99%

Using cloud ice flux to parametrise large-scale lightning

et al. 2014

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Abstract.Lightning is an important natural source of nitrogen oxide especially in the middle and upper troposphere. Hence, it is essential to represent lightning in chemistry transport and coupled chemistry-climate models. Using ERA-Interim meteorological reanalysis data we compare the lightning flash density distributions produced using several existing lightning parametrisations, as well as a new parametrisation developed on the basis of upward cloud ice flux at 440 hPa. The use of ice flux forms a link to the non-inductive charging mechanism of thunderstorms. Spatial and temporal distributions of lightning flash density are compared to tropical and subtropical observations for 2007-2011 from the Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite. The well-used lightning flash parametrisation based on cloud-top height has large biases but the derived annual total flash density has a better spatial correlation with the LIS observations than other existing parametrisations. A comparison of flash density simulated by the different schemes shows that the cloud-top height parametrisation has many more instances of moderate flash densities and fewer low and high extremes compared to the other parametrisations. Other studies in the literature have shown that this feature of the cloud-top height parametrisation is in contrast to lightning observations over certain regions. Our new ice flux parametrisation shows a clear improvement over all the existing parametrisations with lower root mean square errors (RMSEs) and better spatial correlations with the observations for distributions of annual total, and seasonal and interannual variations. The greatest improvement with the new parametrisation is a more realistic representation of the zonal distribution with a better balance between tropical and subtropical lightning flash estimates. The new parametrisation is appropriate for testing in chemistry transport and chemistry-climate models that use a lightning parametrisation.

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“…A similar criterion was used in Wang, Rossow, and Zhang (2000) using radiosonde data. Despite the fact that the cloud filter was successfully applied to radiosonde data, in numerical weather prediction the results may present some bias when performing comparison to in situ measurements or sounder profiles derived from satellites (Boilley and Wald 2015;Schreier et al 2014). After application of the cloud filter, the total number of atmospheric profiles was reduced to 8324 (4714 over land and 3610 over sea).…”

Section: Spatial Distributionmentioning

confidence: 98%

Global Atmospheric Profiles from Reanalysis Information (GAPRI): a new database for earth surface temperature retrieval

Mattar

Durán‐Alarcón

Jiménez-Muñoz

et al. 2015

International Journal of Remote Sensing

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Artículo de publicación ISISin acceso a texto completoThis paper presents the Global Atmospheric Profiles derived from Reanalysis Information (GAPRI) database, which was designed for earth surface temperature retrieval. GAPRI is a comprehensive compilation of selected atmospheric vertical profiles at global scale which can be used for radiative transfer simulation in order to obtain generalized algorithms to estimate land surface temperature (LST). GAPRI includes information on geopotential height, atmospheric pressure, air temperature, and relative humidity derived from the European Centre for Medium-Range Weather Forecasts Re-Analysis data from year 2011. The atmospheric profiles are structured for 29 vertical levels and extracted from a global spatial grid of about 0.75 degrees x 0.75 degrees latitude-longitude with a temporal resolution of 6hours. The selection method is based in the extraction of clear sky profiles over different atmospheric weather conditions such as tropical, mid-latitude summer, subarctic, and arctic, while also considering sea and land areas and day- and night-time conditions. The GAPRI database was validated by comparing land and sea surface temperature values derived from it to those obtained using other existing atmospheric profile databases and in situ measurements. Moreover, GAPRI was also compared to previous radiosonde atmospheric profiles using simulated split-window algorithms. Results show good agreement between GAPRI and previous atmospheric databases, thus demonstrating the potential of GAPRI for studies related to forward simulations in the thermal infrared range. GAPRI is a freely available database that can be modified according to the user's needs and local atmospheric conditionsproject Fondecyt-Initial [CONICYT] 11130359 Ministerio de Economia y Competitividad of Spain [CEOS-Spain] AYA2011-29334-C02-0

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Atmospheric parameters in a subtropical cloud regime transition derived by AIRS and MODIS: observed statistical variability compared to ERA-Interim

Cited by 14 publications

References 66 publications

Comparisons of the tropospheric specific humidity from GPS radio occultations with ERA–Interim, NASA MERRA and AIRS data

Comparisons of the tropospheric specific humidity from GPS radio occultations with ERA–Interim, NASA MERRA and AIRS data

Using cloud ice flux to parametrise large-scale lightning

Global Atmospheric Profiles from Reanalysis Information (GAPRI): a new database for earth surface temperature retrieval

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