scholarly journals Characterizing Sampling and Quality Screening Biases in Infrared and Microwave Limb Sounding

2017 ◽  
Author(s):  
Luis F. Millán ◽  
Nathaniel J. Livesey ◽  
Michelle L. Santee ◽  
Thomas von Clarmann

Abstract. This study investigates orbital sampling biases and evaluates the additional impact caused by data quality screening for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and the Aura Microwave Limb Sounder (MLS). MIPAS acts as a proxy for typical infrared limb emission sounders, while MLS acts as a proxy for microwave limb sounders. These biases were calculated for temperature and several trace gases by interpolating model fields to real sampling patterns and, additionally, screening those locations as directed by their corresponding quality criteria. Both instruments have dense uniform sampling patterns typical of limb emission sounders, producing almost identical sampling biases. However, there is a substantial difference between the number of locations discarded. MIPAS, as a mid-infrared instrument, is very sensitive to clouds, and measurements affected by them are thus rejected from the analysis. For example, in the tropics, the MIPAS yield is strongly affected by clouds, while MLS is mostly unaffected. The results show that upper tropospheric sampling biases in zonally averaged data, for both instruments, can be up to 10 % to 30 %, depending on the species, and up to 3 K for temperature. For MIPAS, the sampling reduction due to quality screening worsens the biases, leading to values as large as 30 % to 100 % for the trace gases and expanding the 3 K bias region for temperature. This type of sampling bias is largely induced by the geophysical origins of the screening (e.g. clouds). Further, analysis of long-term time series reveals that these additional quality screening biases may affect the ability to accurately detect upper tropospheric long-term changes using such data. In contrast, MLS data quality screening removes sufficiently few points that no additional bias is introduced, although the vertical range of reliable measurements is slightly reduced. We emphasize that the results of this study refer only to the representativeness of the respective data, not to their intrinsic quality.

2018 ◽  
Vol 18 (6) ◽  
pp. 4187-4199 ◽  
Author(s):  
Luis F. Millán ◽  
Nathaniel J. Livesey ◽  
Michelle L. Santee ◽  
Thomas von Clarmann

Abstract. This study investigates orbital sampling biases and evaluates the additional impact caused by data quality screening for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and the Aura Microwave Limb Sounder (MLS). MIPAS acts as a proxy for typical infrared limb emission sounders, while MLS acts as a proxy for microwave limb sounders. These biases were calculated for temperature and several trace gases by interpolating model fields to real sampling patterns and, additionally, screening those locations as directed by their corresponding quality criteria. Both instruments have dense uniform sampling patterns typical of limb emission sounders, producing almost identical sampling biases. However, there is a substantial difference between the number of locations discarded. MIPAS, as a mid-infrared instrument, is very sensitive to clouds, and measurements affected by them are thus rejected from the analysis. For example, in the tropics, the MIPAS yield is strongly affected by clouds, while MLS is mostly unaffected. The results show that upper-tropospheric sampling biases in zonally averaged data, for both instruments, can be up to 10 to 30 %, depending on the species, and up to 3 K for temperature. For MIPAS, the sampling reduction due to quality screening worsens the biases, leading to values as large as 30 to 100 % for the trace gases and expanding the 3 K bias region for temperature. This type of sampling bias is largely induced by the geophysical origins of the screening (e.g. clouds). Further, analysis of long-term time series reveals that these additional quality screening biases may affect the ability to accurately detect upper-tropospheric long-term changes using such data. In contrast, MLS data quality screening removes sufficiently few points that no additional bias is introduced, although its penetration is limited to the upper troposphere, while MIPAS may cover well into the mid-troposphere in cloud-free scenarios. We emphasize that the results of this study refer only to the representativeness of the respective data, not to their intrinsic quality.


2021 ◽  
Vol 255 ◽  
pp. 108933
Author(s):  
Reinmar Seidler ◽  
Richard B. Primack ◽  
Varun R. Goswami ◽  
Sarala Khaling ◽  
M. Soubadra Devy ◽  
...  

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mateusz Taszarek ◽  
John T. Allen ◽  
Mattia Marchio ◽  
Harold E. Brooks

AbstractGlobally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.


2021 ◽  
Vol 264 ◽  
pp. 112617
Author(s):  
Muhammad Bilal ◽  
Alaa Mhawish ◽  
Janet E. Nichol ◽  
Zhongfeng Qiu ◽  
Majid Nazeer ◽  
...  
Keyword(s):  

2021 ◽  
Author(s):  
Hao Xu ◽  
Xu Lian ◽  
Ingrid Slette ◽  
Hui Yang ◽  
Yuan Zhang ◽  
...  

Abstract The timing and length of the dry season is a key factor governing ecosystem productivity and the carbon cycle of the tropics. Mounting evidence has suggested a lengthening of the dry season with ongoing climate change. However, this conclusion is largely based on changes in precipitation (P) compared to its long-term average (P ̅) and lacks consideration of the simultaneous changes in ecosystem water demand (measured by potential evapotranspiration, Ep, or actual evapotranspiration, E). Using several long-term (1979-2018) observational datasets, we compared changes in tropical dry season length (DSL) and timing (dry season arrival, DSA, and dry season end, DSE) among three common metrics used to define the dry season: P < P ̅, P < Ep, and P < E. We found that all three definitions show that dry seasons have lengthened in much of the tropics since 1979. Among the three definitions, P < E estimates the largest fraction (49.0%) of tropical land area likely experiencing longer dry seasons, followed by P < Ep (41.4%) and P < P ̅ (34.4%). The largest differences in multi-year mean DSL (> 120 days) among the three definitions occurred in the most arid and the most humid regions of the tropics. All definitions and datasets consistently showed longer dry seasons in southern Amazon (due to delayed DSE) and central Africa (due to both earlier DSA and delayed DSE). However, definitions that account for changing water demand estimated longer DSL extension over those two regions. These results indicate that warming-enhanced evapotranspiration exacerbates dry season lengthening and ecosystem water deficit. Thus, it is necessity to account for the evolving water demand of tropical ecosystems when characterizing changes in seasonal dry periods and ecosystem water deficits in an increasingly warmer and drier climate.


2021 ◽  
Author(s):  
Hongfan Yu ◽  
Qingsong Yu ◽  
Yuxian Nie ◽  
Wei Xu ◽  
Yang Pu ◽  
...  

BACKGROUND High-frequent patient-reported outcome (PRO) assessments are used to measure patients’ symptoms after surgery for surgical research; however, quality of those longitudinal PRO data has seldom been discussed. OBJECTIVE To describe errors, to identify factors influencing the data quality, and to profile error trajectories of data longitudinally collected via paper-and-pencil (P&P) or web-based-assessment (ePRO) after thoracic surgery. METHODS We extracted longitudinal PRO data from two prospective clinical studies. PROs were assessed by the MD Anderson Symptom Inventory Lung Cancer Module and single-item Quality of Life Scale before surgery and then daily after surgery until discharge or up to 14 days of hospitalization. Patient compliance and data error were identified and compared between P&P and ePRO. Generalized estimating equations models and two-piecewise models were used to describe trajectories of error incidence over time and to identify the risk factors. RESULTS Among 629 patients with at least 2 PRO assessments, 440 completed 3347 P&P assessments and 189 completed 1291 ePRO assessments. In total, 49.44% of patients had at least 1 error, including 1) missing items (64.69%), 2) modifications without signatures (27.99%), 3) selection of multiple options (3.02%), 4) missing patient signatures (2.54%), 5) missing researcher signatures (1.45%) and 6) missing completion dates (0.3%). ePRO patients had fewer errors than P&P patients (30.16% vs. 57.73%, p <0.0001). Compared with ePRO patients, those using P&P were older, less educated and sicker. Common risk factors of having errors were with a lower education level (P&P, OR=1.39, 95%CL=1.20-1.62, p<.0001; ePRO, OR=1.82, 95%CI=1.22-2.72, p=0.0032), treated in a provincial hospital (P&P, OR=3.34, 95%CI=2.10-5.33, p<.0001; ePRO, OR=4.73, 95%CI=2.18-10.25, p<.0001) and with severe disease (P&P, OR=1.63, 95%CI=1.33-1.99, p<.0001; ePRO, OR=2.70, 95%CI=1.53-4.75, p=0.0006). Errors peaked on postoperative day (POD) 1 for P&P, and on POD 2 for ePRO. CONCLUSIONS ePRO might be superior to P&P in terms of data quality. However, sampling bias needs to be considered for studies using longitudinal PROs as major outcomes.


2016 ◽  
Author(s):  
Norbert Glatthor ◽  
Michael Höpfner ◽  
Adrian Leyser ◽  
Gabriele P. Stiller ◽  
Thomas von Clarmann ◽  
...  

Abstract. We present a global OCS data set covering the period June 2002 to April 2012, derived from FTIR limb emission spectra measured with the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on the ENVISAT satellite. The vertical resolution is 4–5 km in the height region 6–15 km and 15 km at 40 km altitude. The total estimated error amounts to 40–50 pptv between 10 and 20 km and to 120 pptv at 40 km altitude. MIPAS OCS data show no systematic bias with respect to balloon observations, with deviations mostly below ±50 pptv. However, they are systematically higher than the OCS volume mixing ratios of the ACE-FTS instrument on SCISAT, with maximum deviations of up to 100 pptv in the altitude region 13–16 km. The data set of MIPAS OCS exhibits only moderate interannual variations and low interhemispheric differences. Average concentrations at 10 km altitude range from 480 pptv at high latitudes to 500–510 pptv in the tropics and at northern mid-latitudes. Seasonal variations at 10 km altitude amount up to 35 pptv in the northern and up to 15 pptv in the southern hemisphere. Northern hemispheric OCS abundances at 10 km altitude peak in June in the tropics and around October at high latitudes, while the respective southern hemispheric maxima were observed in July and in November. Global OCS distributions at 250 hPa (~ 10–11 km) show enhanced values at low latitudes, peaking during boreal summer above the western Pacific and the Indian Ocean, which indicates oceanic release. Further, a region of depleted OCS amounts extending from Brazil to central and southern Africa was detected at this altitude, which is most pronounced in austral summer. This depletion is related to seasonally varying vegetative uptake by the tropical forests. Typical signatures of biomass burning like the southern hemispheric biomass burning plume are not visible in MIPAS data, indicating that this process is only a minor source of tropospheric OCS. At the 150 hPa level (~ 13–14 km) enhanced amounts of OCS were also observed inside the Asian Monsoon Anticyclone, but this enhancement is not especially outstanding as compared to other low latitude regions at the same altitude. At the 80 hPa level (~ 17–18 km) equatorward transport of mid-latitude air masses containing lower OCS amounts around the summertime anticyclones was observed. A significant trend could not be detected in tropospheric MIPAS OCS amounts, which points to globally balanced sources and sinks.


2017 ◽  
Vol 17 (18) ◽  
pp. 11521-11539 ◽  
Author(s):  
Stefan Lossow ◽  
Hella Garny ◽  
Patrick Jöckel

Abstract. The amplitude of the annual variation in water vapour exhibits a distinct isolated maximum in the middle and upper stratosphere in the southern tropics and subtropics, peaking typically around 15° S in latitude and close to 3 hPa (∼  40.5 km) in altitude. This enhanced annual variation is primarily related to the Brewer–Dobson circulation and hence also visible in other trace gases. So far this feature has not gained much attention in the literature and the present work aims to add more prominence. Using Envisat/MIPAS (Environmental Satellite/Michelson Interferometer for Passive Atmospheric Sounding) observations and ECHAM/MESSy (European Centre for Medium-Range Weather Forecasts Hamburg/Modular Earth Submodel System) Atmospheric Chemistry (EMAC) simulations we provide a dedicated illustration and a full account of the reasons for this enhanced annual variation.


2018 ◽  
Vol 11 (8) ◽  
pp. 4693-4705 ◽  
Author(s):  
Alexandra Laeng ◽  
Ellen Eckert ◽  
Thomas von Clarmann ◽  
Michael Kiefer ◽  
Daan Hubert ◽  
...  

Abstract. The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) was an infrared limb emission spectrometer on the Envisat platform. From 2002 to 2012, it performed pole-to-pole measurements during day and night, producing more than 1000 profiles per day. The European Space Agency (ESA) recently released the new version 7 of Level 1B MIPAS spectra, in which a new set of time-dependent correction coefficients for the nonlinearity in the detector response functions was implemented. This change is expected to reduce the long-term drift of the MIPAS Level 2 data. We evaluate the long-term stability of ozone Level 2 data retrieved from MIPAS v7 Level 1B spectra with the IMK/IAA scientific level 2 processor. For this, we compare MIPAS data with ozone measurements from the Microwave Limb Sounder (MLS) instrument on NASA's Aura satellite, ozonesondes and ground-based lidar instruments. The ozonesondes and lidars alone do not allow us to conclude with enough significance that the new version is more stable than the previous one, but a clear improvement in long-term stability is observed in the satellite-data-based drift analysis. The results of ozonesondes, lidars and satellite drift analysis are consistent: all indicate that the drifts of the new version are less negative/more positive nearly everywhere above 15 km. The 10-year MIPAS ozone trends calculated from the old and the new data versions are compared. The new trends are closer to old drift-corrected trends than the old uncorrected trends were. From this, we conclude that the nonlinearity correction performed on Level 1B data is an improvement. These results indicate that MIPAS data are now even more suited for trend studies, alone or as part of a merged data record.


2018 ◽  
Author(s):  
Anne Boynard ◽  
Daniel Hurtmans ◽  
Katerina Garane ◽  
Florence Goutail ◽  
Juliette Hadji-Lazaro ◽  
...  

Abstract. This paper assesses the quality of IASI/Metop-A (IASI-A) and IASI/Metop-B (IASI-B) ozone (O3) products (total and partial O3 columns) retrieved with the Fast Optimal Retrievals on Layers for IASI Ozone (FORLI-O3) v20151001 software for nine years (2008–2017) through an extensive inter-comparison and validation exercise using independent observations (satellite, ground-based and ozonesonde). IASI-A and IASI-B Total O3 Columns (TOCs) are generally consistent, with a global mean difference less than 0.3 % for both day- and nighttime measurements, IASI-A being slightly higher than IASI-B. A global difference less than 2.4 % is found for the tropospheric (TROPO) O3 column product (IASI-A being lower than IASI-B), which is partly due to a temporary issue related to IASI-A viewing angle in 2015. Our validation shows that IASI-A and IASI-B TOCs are consistent with GOME-2, Dobson, Brewer and SAOZ retrieved ones, with global mean differences in the range 0.1–2 % depending on the instruments. The IASI-A and ground-based TOC comparison for the period 2008–July 2017 shows good long-term stability (negative trends within 3 % decade−1). The comparison results between IASI-A and IASI-B against smoothed ozonesonde partial O3 columns vary in altitude and latitude, with maximum standard deviation for the 300–150 hPa column (20–40 %) due to strong ozone variability and a priori uncertainty. The worst agreement with the ozonesondes and with UV-vis retrieved TOC [satellite and ground] is found at the southern high latitudes. Compared to ozonesonde data, IASI-A and IASI-B O3 products overestimate the O3 abundance in the stratosphere (up to 20 % for the 150–25 hPa column) and underestimates the O3 abundance in the troposphere (within 10 % for the mid-latitudes and ~ 18 % for the tropics). Based on the period 2011–2016, non-significant drift is found for the northern hemispheric tropospheric columns while a small drift prevails for the period before 2011.


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