Diagnostics for Evaluating the Impact of Satellite Observations

Author(s):  
Nancy L. Baker ◽  
Rolf H. Langland
2016 ◽  
Author(s):  
M. Venkat Ratnam ◽  
S. Ravindra Babu ◽  
S. S. Das ◽  
Ghouse Basha ◽  
B. V. Krishnamurthy ◽  
...  

Abstract. Tropical cyclones play an important role in modifying the tropopause structure and dynamics as well as stratosphere-troposphere exchange (STE) process in the Upper Troposphere and Lower Stratosphere (UTLS) region. In the present study, the impact of cyclones that occurred over the North Indian Ocean during 2007–2013 on the STE process is quantified using satellite observations. Tropopause characteristics during cyclones are obtained from the Global Positioning System (GPS) Radio Occultation (RO) measurements and ozone and water vapor concentrations in UTLS region are obtained from Aura-Microwave Limb Sounder (MLS) satellite observations. The effect of cyclones on the tropopause parameters is observed to be more prominent within 500 km from the centre of cyclone. In our earlier study we have observed decrease (increase) in the tropopause altitude (temperature) up to 0.6 km (3 K) and the convective outflow level increased up to 2 km. This change leads to a total increase in the tropical tropopause layer (TTL) thickness of 3 km within the 500 km from the centre of cyclone. Interestingly, an enhancement in the ozone mixing ratio in the upper troposphere is clearly noticed within 500 km from cyclone centre whereas the enhancement in the water vapor in the lower stratosphere is more significant on south-east side extending from 500–1000 km away from the cyclone centre. We estimated the cross-tropopause mass flux for different intensities of cyclones and found that the mean flux from stratosphere to troposphere for cyclonic stroms is 0.05 ± 0.29 × 10−3 kg m−2 and for very severe cyclonic stroms it is 0.5 ± 1.07 × 10−3 kg m−2. More downward flux is noticed in the north-west and south-west side of the cyclone centre. These results indicate that the cyclones have significant impact in effecting the tropopause structure, ozone and water vapour budget and consequentially the STE in the UTLS region.


2007 ◽  
Vol 4 (3) ◽  
pp. 1877-1921 ◽  
Author(s):  
B. Schneider ◽  
L. Bopp ◽  
M. Gehlen ◽  
J. Segschneider ◽  
T. L. Frölicher ◽  
...  

Abstract. This study compares spatial and temporal variability in net primary productivity (PP) and particulate organic carbon (POC) export production (EP) from three different coupled climate carbon cycle models (IPSL, MPIM, NCAR) with observation-based estimates derived from satellite measurements of ocean colour and inverse modelling. Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006)\\nocite{Behrenfeld06} with stronger stratification (higher SSTs) leading to negative PP anomalies and vice versa. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for global PP anomalies. Two of the models also reproduce the inverse relationship between stratification (SST) and PP, especially in the equatorial Pacific. With the help of the model results we are able to explain the chain of cause and effect leading from stratification (SST) through nutrient concentrations to PP and finally to EP. There are significant uncertainties in observational PP and especially EP. Our finding of a good agreement between independent estimates from coupled models and satellite observations provides increased confidence that such models can be used as a first basis to estimate the impact of future climate change on marine productivity and carbon export.


2018 ◽  
Vol 373 (1760) ◽  
pp. 20170407 ◽  
Author(s):  
Paul I. Palmer

The 2015/2016 El Niño was the first major climate variation when there were a range of satellite observations that simultaneously observed land, ocean and atmospheric properties associated with the carbon cycle. These data are beginning to provide new insights into the varied responses of land ecosystems to El Niño, but we are far from fully exploiting the information embodied by these data. Here, we briefly review the atmospheric and terrestrial satellite data that are available to study the carbon cycle. We also outline recommendations for future research, particularly the closer integration of satellite data with forest biometric datasets that provide detailed information about carbon dynamics on a range of timescales. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.


2021 ◽  
Author(s):  
Zoe Davis ◽  
Debora Griffin ◽  
Yue Jia ◽  
Susann Tegtmeier ◽  
Mallory Loria ◽  
...  

<p>A recent method uses satellite measurements to estimate lifetimes and emissions of trace-gases from point sources (Fioletov et al., 2015). Emissions are retrieved by fitting measured vertical column densities (VCDs) of trace-gases to a three-dimensional function of the wind speed and spatial coordinates. In this study, a plume model generated “synthetic” satellite observations of prescribed emissions to examine the accuracy of the retrieved emissions. The Lagrangian transport and dispersion model FLEXPART (v10.0) modelled the plume from a point source over a multi-day simulation period at a resolution much higher than current satellite observations. The study aims to determine how various assumptions in the retrieval method and local meteorological conditions affect the accuracy and precision of emissions. These assumptions include that the use of a vertical mean of the wind profile is representative of the transport of the plume’s vertical column. In the retrieval method, the VCDs’ pixel locations are rotated around the source based on wind direction so that all plumes have a common wind direction. Retrievals using a vertical mean wind for rotation will be compared to retrievals using VCDs determined by rotating each altitude of the vertical profile of trace-gas using the respective wind-direction. The impact of local meteorological factors on the two approaches will be presented, including atmospheric mixing, vertical wind shear, and boundary layer height. The study aims to suggest which altitude(s) of the vertical profile of winds results in the most accurate retrievals given the local meteorological conditions. The study will also examine the impact on retrieval accuracy due to satellite resolution, trace-gas lifetime, plume source altitude, number of overpasses, and random and systematic errors. Sensitivity studies repeated using a second, “line-density”, retrieval method will also be presented (Adams et al., 2019; Goldberg et al., 2019).</p>


2009 ◽  
Vol 137 (1) ◽  
pp. 41-50 ◽  
Author(s):  
James S. Goerss

Abstract The tropical cyclone (TC) track forecasts of the Navy Operational Global Atmospheric Prediction System (NOGAPS) were evaluated for a number of data assimilation experiments conducted using observational data from two periods: 4 July–31 October 2005 and 1 August–30 September 2006. The experiments were designed to illustrate the impact of different types of satellite observations on the NOGAPS TC track forecasts. The satellite observations assimilated in these experiments consisted of feature-track winds from geostationary and polar-orbiting satellites, Special Sensor Microwave Imager (SSM/I) total column precipitable water and wind speeds, Advanced Microwave Sounding Unit-A (AMSU-A) radiances, and Quick Scatterometer (QuikSCAT) and European Remote Sensing Satellite-2 (ERS-2) scatterometer winds. There were some differences between the results from basin to basin and from year to year, but the combined results for the 2005 and 2006 test periods for the North Pacific and Atlantic Ocean basins indicated that the assimilation of the feature-track winds from the geostationary satellites had the most impact, ranging from 7% to 24% improvement in NOGAPS TC track forecasts. This impact was statistically significant at all forecast lengths. The impact of the assimilation of SSM/I precipitable water was consistently positive and statistically significant at all forecast lengths. The improvements resulting from the assimilation of AMSU-A radiances were also consistently positive and significant at most forecast lengths. There were no significant improvements/degradations from the assimilation of the other satellite observation types [e.g., Moderate Resolution Imaging Spectroradiometer (MODIS) winds, SSM/I wind speeds, and scatterometer winds]. The assimilation of all satellite observations resulted in a gain in skill of roughly 12 h for the NOGAPS 48- and 72-h TC track forecasts and a gain in skill of roughly 24 h for the 96- and 120-h forecasts. The percent improvement in these forecasts ranged from almost 20% at 24 h to over 40% at 120 h.


2017 ◽  
Vol 30 (1) ◽  
pp. 91-107 ◽  
Author(s):  
Qingtao Song ◽  
Dudley B. Chelton ◽  
Steven K. Esbensen ◽  
Andrew R. Brown

This study presents an assessment of the impact of a March 2006 change in the Met Office operational global numerical weather prediction model through the introduction of a nonlocal momentum mixing scheme. From comparisons with satellite observations of surface wind speed and sea surface temperature (SST), it is concluded that the new parameterization had a relatively minor impact on SST-induced changes in sea surface wind speed in the Met Office model in the September and October 2007 monthly averages over the Agulhas Return Current region considered here. The performance of the new parameterization of vertical mixing was evaluated near the surface layer and further through comparisons with results obtained using a wide range of sensitivity of mixing parameterization to stability in the Weather Research and Forecasting (WRF) Model, which is easily adapted to such sensitivity studies. While the new parameterization of vertical mixing improves the Met Office model response to SST in highly unstable (convective) conditions, it is concluded that significantly enhanced vertical mixing in the neutral to moderately unstable conditions (nondimensional stability [Formula: see text] between 0 and −2) typically found over the ocean is required in order for the model surface wind response to SST to match the satellite observations. Likewise, the reduced mixing in stable conditions in the new parameterization is also relatively small; for the range of the gradient Richardson number typically found over the ocean, the mixing was reduced by a maximum of only 10%, which is too small by more than an order of magnitude to be consistent with the satellite observations.


2017 ◽  
Vol 17 (13) ◽  
pp. 8395-8410 ◽  
Author(s):  
Habib Senghor ◽  
Éric Machu ◽  
Frédéric Hourdin ◽  
Amadou Thierno Gaye

Abstract. The impact of desert aerosols on climate, atmospheric processes, and the environment is still debated in the scientific community. The extent of their influence remains to be determined and particularly requires a better understanding of the variability of their distribution. In this work, we studied the variability of these aerosols in western Africa using different types of satellite observations. SeaWiFS (Sea-Viewing Wide Field-of-View Sensor) and OMI (Ozone Monitoring Instrument) data have been used to characterize the spatial distribution of mineral aerosols from their optical and physical properties over the period 2005–2010. In particular, we focused on the variability of the transition between continental western African and the eastern Atlantic Ocean. Data provided by the lidar scrolling CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) onboard the satellite CALIPSO (Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations) for the period 2007–2013 were then used to assess the seasonal variability of the vertical distribution of desert aerosols. We first obtained a good representation of aerosol optical depth (AOD) and single-scattering albedo (SSA) from the satellites SeaWiFS and OMI, respectively, in comparison with AERONET estimates, both above the continent and the ocean. Dust occurrence frequency is higher in spring and boreal summer. In spring, the highest occurrences are located between the surface and 3 km above sea level, while in summer the highest occurrences are between 2 and 5 km altitude. The vertical distribution given by CALIOP also highlights an abrupt change at the coast from spring to fall with a layer of desert aerosols confined in an atmospheric layer uplifted from the surface of the ocean. This uplift of the aerosol layer above the ocean contrasts with the winter season during which mineral aerosols are confined in the atmospheric boundary layer. Radiosondes at Dakar Weather Station (17.5° W, 14.74° N) provide basic thermodynamic variables which partially give a causal relationship between the layering of the atmospheric circulation over western Africa and their aerosol contents throughout the year. A SSA increase is observed in winter and spring at the transition between the continent and the ocean. The analysis of mean NCEP (National Centers for Environmental Prediction) winds at 925 hPa between 2000 and 2012 suggest a significant contribution of coastal sand sources from Mauritania in winter which would increase SSA over the ocean.


2020 ◽  
Author(s):  
Claire Lamotte ◽  
Virginie Marécal ◽  
Jonathan Guth

<p>Constraining emission inventories into chemistry-transport models (CTM) is essential. In addition to anthropogenic emissions, natural sources of pollutants must be considered. Among them, volcanoes are large emitters of gases, including sulfur dioxide (SO<sub>2</sub>), a volatile species, causing environmental and health issues.</p><p>Volcanic SO<sub>2</sub> emission inventories are usually integrated in global CTMs, in order to improve the modelling of chemical species in the atmosphere. Here, we use the model MOCAGE, developed at CNRM, which currently uses Andres & Krasgnoc’s inventory (1998); a temporal average of emission on some 40 volcanoes, monitored through the synergy of satellite data and surface remote sensing instruments, for 25 years (from 1970’s to 1997). However, this inventory is now quite old and is therefore no longer sufficiently accurate.</p><p>Thanks to the development of new satellite observations, it has become possible to produce such inventories with an improved accuracy. The global coverage and higher sensitivity of these instruments has allowed to reference more emission sources (hard-to-access volcanoes, small eruptions or even passive degassing). Hence, a new inventory of Carn et al (2016,2017) based on satellite observations has been implemented in MOCAGE. Besides being recent (from 1978 up to 2015), it combines eruption and passive degassing over more than 160 volcanoes. Passive degassing fluxes are provided as annual averages and eruption fluxes as daily total quantities (in case of events). In addition, information on volcanoes vent altitude and eruptive plume heights is available, which has been used to better constraints the model.</p><p>We focus our study at the global scale. The years 2013 and 2014 were chosen as the years with the lowest and highest total eruptive emissions respectively, in Carn's inventory. Thus, 2013 highlights mainly the impact of passive degassing, while 2014 provides additional information on eruptions.</p><p>For each of the years studied, the sulfur species budget in MOCAGE simulation is increased when the inventory is updated and therefore the relative contribution of volcanic sulfur emissions is larger. We note the global increase in sulfur dioxide and sulfate aerosol burdens; an increase even more significant when the injection heights of the emissions are taken into account.</p>


2011 ◽  
Vol 116 (D15) ◽  
Author(s):  
Zhe Jiang ◽  
Dylan B. A. Jones ◽  
Monika Kopacz ◽  
Jane Liu ◽  
Daven K. Henze ◽  
...  

2013 ◽  
Vol 13 (14) ◽  
pp. 6687-6711 ◽  
Author(s):  
M. J. Alvarado ◽  
V. H. Payne ◽  
E. J. Mlawer ◽  
G. Uymin ◽  
M. W. Shephard ◽  
...  

Abstract. Modern data assimilation algorithms depend on accurate infrared spectroscopy in order to make use of the information related to temperature, water vapor (H2O), and other trace gases provided by satellite observations. Reducing the uncertainties in our knowledge of spectroscopic line parameters and continuum absorption is thus important to improve the application of satellite data to weather forecasting. Here we present the results of a rigorous validation of spectroscopic updates to an advanced radiative transfer model, the Line-By-Line Radiative Transfer Model (LBLRTM), against a global dataset of 120 near-nadir, over-ocean, nighttime spectra from the Infrared Atmospheric Sounding Interferometer (IASI). We compare calculations from the latest version of LBLRTM (v12.1) to those from a previous version (v9.4+) to determine the impact of spectroscopic updates to the model on spectral residuals as well as retrieved temperature and H2O profiles. We show that the spectroscopy in the CO2 ν2 and ν3 bands is significantly improved in LBLRTM v12.1 relative to v9.4+, and that these spectroscopic updates lead to mean changes of ~0.5 K in the retrieved vertical temperature profiles between the surface and 10 hPa, with the sign of the change and the variability among cases depending on altitude. We also find that temperature retrievals using each of these two CO2 bands are remarkably consistent in LBLRTM v12.1, potentially allowing these bands to be used to retrieve atmospheric temperature simultaneously. The updated H2O spectroscopy in LBLRTM v12.1 substantially improves the a posteriori residuals in the P-branch of the H2O ν2 band, while the improvements in the R-branch are more modest. The H2O amounts retrieved with LBLRTM v12.1 are on average 14% lower between 100 and 200 hPa, 42% higher near 562 hPa, and 31% higher near the surface compared to the amounts retrieved with v9.4+ due to a combination of the different retrieved temperature profiles and the updated H2O spectroscopy. We also find that the use of a fixed ratio of HDO to H2O in LBLRTM may be responsible for a significant fraction of the remaining bias in the P-branch relative to the R-branch of the H2O ν2 band. There were no changes to O3 spectroscopy between the two model versions, and so both versions give positive a posteriori residuals of ~ 0.3 K in the R-branch of the O3 ν3 band. While the updates to the H2O self-continuum employed by LBLRTM v12.1 have clearly improved the match with observations near the CO2 ν3 band head, we find that these updates have significantly degraded the match with observations in the fundamental band of CO. Finally, significant systematic a posteriori residuals remain in the ν4 band of CH4, but the magnitude of the positive bias in the retrieved mixing ratios is reduced in LBLRTM v12.1, suggesting that the updated spectroscopy could improve retrievals of CH4 from satellite observations.


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