scholarly journals On the Semidiurnal Variation in Surface Rainfall Rate over the Tropics in a Global Cloud-Rresolving Model Simulation and Satellite Observations

2021 ◽  
Author(s):  
Toshiro INOUE ◽  
Kavirajan RAJENDRAN ◽  
Masaki SATOH ◽  
Hiroaki MIURA
Keyword(s):  
Model Simulation ◽  
Satellite Observations ◽  
Rainfall Rate ◽  
Surface Rainfall ◽  
Semidiurnal Variation ◽  
The Tropics

scholarly journals Evaluation of near-tropopause ozone distributions in the Global Modeling Initiative combined stratosphere/troposphere model with ozonesonde data

2008 ◽  
Vol 8 (1) ◽  
pp. 1589-1634 ◽  
Author(s):  
D. B. Considine ◽  
J. A. Logan ◽  
M. A. Olsen
Keyword(s):  
Annual Cycle ◽  
Transport Model ◽  
Model Simulation ◽  
Atmospheric Composition ◽  
Vertical Resolution ◽  
Residual Circulation ◽  
Vertical Diffusion ◽  
Global Modeling ◽  
Upper Troposphere ◽  
The Tropics

Abstract. The NASA Global Modeling Initiative has developed a combined stratosphere/troposphere chemistry and transport model which fully represents the processes governing atmospheric composition near the tropopause. We evaluate model ozone distributions near the tropopause, using two high vertical resolution monthly mean ozone profile climatologies constructed with ozonesonde data, one by averaging on pressure levels and the other relative to the thermal tropopause. Model ozone is high-biased at the SH tropical and NH midlatitude tropopause by ~45% in a 4° latitude × 5° longitude model simulation. Increasing the resolution to 2°×2.5&amp;deg increases the NH tropopause high bias to ~60%, but decreases the tropical tropopause bias to ~30%, an effect of a better-resolved residual circulation. The tropopause ozone biases appear not to be due to an overly vigorous residual circulation or excessive stratosphere/troposphere exchange, but are more likely due to insufficient vertical resolution or excessive vertical diffusion near the tropopause. In the upper troposphere and lower stratosphere, model/measurement intercomparisons are strongly affected by the averaging technique. NH and tropical mean model lower stratospheric biases are <20%. In the upper troposphere, the 2°×2.5&amp;deg simulation exhibits mean high biases of ~20% and~35% during April in the tropics and NH midlatitudes, respectively, compared to the pressure-averaged climatology. However, relative-to-tropopause averaging produces upper troposphere high biases of ~30% and 70% in the tropics and NH midlatitudes. This is because relative-to-tropopause averaging better preserves large cross-tropopause O3 gradients, which are seen in the daily sonde data, but not in daily model profiles. The relative annual cycle of ozone near the tropopause is reproduced very well in the model Northern Hemisphere midlatitudes. In the tropics, the model amplitude of the near-tropopause annual cycle is weak. This is likely due to the annual amplitude of mean vertical upwelling near the tropopause, which analysis suggests is ~30% weaker than in the real atmosphere.

Intercomparison of Phytoplankton functional types dynamics from satellite observations

2021 ◽  
Author(s):  
Marine Bretagnon ◽  
Séverine Alvain ◽  
Astrid Bracher ◽  
Philippe Garnesson ◽  
Svetlana losa ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Marine Environment ◽  
Model Simulation ◽  
Chlorophyll Concentration ◽  
Satellite Observations ◽  
Global Ocean ◽  
Ocean Colour ◽  
Marginal Seas ◽  
Functional Types ◽  
Wide Range

&lt;p&gt;Copernicus marine environment monitoring service (CMEMS) gives users access to a wide range of ocean descriptors. Both physics and biogeochemistry of the marine environment can be studied with complementary source of data, such as in situ data, modelling output and satellite observations at global scale and/or for European marginal seas. Among the ocean descriptors supplied as part of CMEMS, phytoplankton functional types (PFTs) describe the phytoplanktonic composition at global level or over European marginal seas. Studied phytoplankton assemblage is particularly important as it is the basis of the marine food-web. Composition of the first trophic level is a valuable indicator to infer the structure of the ecosystem and its health. Over the last decades, ocean colour remote sensing has been used to estimate the phytoplanktonic composition. The algorithms developed to estimate PFTs composition based on ocean colour observation can be classified in three categories: the spectral approaches, the abundance-based approaches (derived from the chlorophyll concentration) and the ecological approaches. The three approaches can lead to differences or, conversely, to similar patterns. Difference and similarity in PFTs estimation from remote sensing is a useful information for data assimilation or model simulation, as it provides indications on the uncertainties/variability associated to the PFT estimates. Indeed, PFT estimates from satellite observations are increasingly assimilated into ecological models to improve biogeochemical simulations, what highlights the importance to get an index or at least information describing the validity range of such PFTs estimates.&lt;/p&gt;&lt;p&gt;In this study, four algorithms (two abundance-based, and two spectral approaches) are compared. The aim of this study is to compare the related PFT products spatially and temporally, and to study the agreement of their derived PFT phenology. This study proposes also to compare PFT algorithms developed for the global ocean with those developed for specific regions in order to assess the potential strength and weakness of the different approaches. Once similarities and discrepancies between the different approaches are assessed, this information could be used by model to give an interval of confidence in model simulation.&lt;/p&gt;

scholarly journals Comparison of Precipitation Derived from the ECMWF Operational Forecast Model and Satellite Precipitation Datasets

2013 ◽  
Vol 14 (5) ◽  
pp. 1463-1482 ◽  
Author(s):  
Chris Kidd ◽  
Erin Dawkins ◽  
George Huffman
Keyword(s):  
Hydrological Modeling ◽  
Model Simulation ◽  
Model Performance ◽  
Tropical Rainfall Measuring Mission ◽  
Forecast Model ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
Diurnal Rainfall ◽  
The Tropics ◽  
Ecmwf Model

Abstract Precipitation is an important component of the climate system, and the accurate representation of the diurnal rainfall cycle is a key test of model performance. Although the modeling of precipitation in the cooler midlatitudes has improved, in the tropics substantial errors still occur. Precipitation from the operational ECMWF forecast model is compared with satellite-derived products from the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) and TRMM Precipitation Radar (PR) to assess the mean annual and seasonal diurnal rainfall cycles. The analysis encompasses the global tropics and subtropics (40°N–40°S) over a 7-yr period from 2004 to 2011. The primary aim of the paper is to evaluate the ability of an operational numerical model and satellite products to retrieve subdaily rainfall. It was found that during the first half of the analysis period the ECMWF model overestimated precipitation by up to 15% in the tropics, although after the implementation of a new convective parameterization in November 2007 this bias fell to about 4%. The ECMWF model poorly represented the diurnal cycle, simulating rainfall too early compared to the TMPA and TRMM PR products; the model simulation of precipitation was particularly poor over Indonesia. In addition, the model did not appear to simulate mountain-slope breezes well or adequately capture many of the characteristics of mesoscale convective systems. The work highlights areas for further study to improve the representation of subgrid-scale processes in parameterization schemes and improvements in model resolution. In particular, the proper representation of subdaily precipitation in models is critical for hydrological modeling and flow forecasting.

scholarly journals The response of the equatorial tropospheric ozone to the Madden–Julian Oscillation in TES satellite observations and CAM-chem model simulation

2014 ◽  
Vol 14 (21) ◽  
pp. 11775-11790 ◽  
Author(s):  
W. Sun ◽  
P. Hess ◽  
B. Tian
Keyword(s):  
Tropospheric Ozone ◽  
Large Scale ◽  
Transport Model ◽  
Model Simulation ◽  
General Pattern ◽  
Phase Speed ◽  
Satellite Observations ◽  
Madden Julian Oscillation ◽  
Dominant Form ◽  
Total Column Ozone

Abstract. The Madden–Julian Oscillation (MJO) is the dominant form of the atmospheric intra-seasonal oscillation, manifested by slow eastward movement (about 5 m s−1) of tropical deep convection. This study investigates the MJO's impact on equatorial tropospheric ozone (10° N–10° S) in satellite observations and chemical transport model (CTM) simulations. For the satellite observations, we analyze the Tropospheric Emission Spectrometer (TES) level-2 ozone profile data for the period of January 2004 to June 2009. For the CTM simulations, we run the Community Atmosphere Model with chemistry (CAM-chem) driven by the Goddard Earth Observing System Model, Version 5 (GEOS-5)-analyzed meteorological fields for the same data period as the TES measurements. Our analysis indicates that the behavior of the total tropospheric column (TTC) ozone at the intra-seasonal timescale is different from that of the total column ozone, with the signal in the equatorial region comparable with that in the subtropics. The model-simulated and satellite-measured ozone anomalies agree in their general pattern and amplitude when examined in the vertical cross section (the average spatial correlation coefficient among the eight phases is 0.63), with an eastward propagation signature at a similar phase speed as the convective anomalies (5 m s−1). The model ozone anomalies on the intra-seasonal timescale are about 5 times larger when lightning emissions of NOx are included in the simulation than when they are not. Nevertheless, large-scale advection is the primary driving force for the ozone anomalies associated with the MJO. The variability related to the MJO for ozone reaches up to 47% of the total variability (ranging from daily to interannual), indicating that the MJO should be accounted for in simulating ozone perturbations in the tropics.

scholarly journals Evaluation of near-tropopause ozone distributions in the Global Modeling Initiative combined stratosphere/troposphere model with ozonesonde data

2008 ◽  
Vol 8 (9) ◽  
pp. 2365-2385 ◽  
Author(s):  
D. B. Considine ◽  
J. A. Logan ◽  
M. A. Olsen
Keyword(s):  
Annual Cycle ◽  
Transport Model ◽  
Model Simulation ◽  
Atmospheric Composition ◽  
Vertical Resolution ◽  
Residual Circulation ◽  
Global Modeling ◽  
Upper Troposphere ◽  
The Tropics ◽  
Model Measurement

Abstract. The NASA Global Modeling Initiative has developed a combined stratosphere/troposphere chemistry and transport model which fully represents the processes governing atmospheric composition near the tropopause. We evaluate model ozone distributions near the tropopause, using two high vertical resolution monthly mean ozone profile climatologies constructed with ozonesonde data, one by averaging on pressure levels and the other relative to the thermal tropopause. At the tropopause, model ozone is high-biased in the SH tropics and NH midlatitudes by ~45% in a 4° latitude ×5° longitude model simulation. Doubling the resolution to 2°×2.5° increases the NH high bias to ~60%, and reduces the tropical bias to ~30%, apparently due to decreased horizontal transport between the tropics and extratropics in the higher-resolution simulation. These ozone biases do not appear to be due to an overly vigorous residual circulation, insufficient convection, or excessive stratosphere/troposphere exchange, and so may be due to insufficient vertical resolution or excessive vertical diffusion near the tropopause. In the upper troposphere and lower stratosphere, model/measurement intercomparisons are strongly affected by the averaging technique. Compared to the pressure-averaged climatology, NH and tropical mean model lower stratospheric biases are >20%. In the upper troposphere, the 2°×2.5° simulation shows mean high biases of ~20% and ~35% during April in the tropics and NH midlatitudes, respectively. This apparently good model/measurement agreement degrades when relative-to-tropopause averages are considered, with upper troposphere high biases of ~30% and 70% in the tropics and NH midlatitudes. This occurs because relative-to-tropopause averaging better preserves the larger cross-tropopause O3 gradients which are seen in the daily sonde data, but not in daily model profiles. Relative-to-tropopause averages therefore more accurately reveal model/measurement discrepancies. The relative annual cycle of ozone near the tropopause is reproduced very well in the model Northern Hemisphere midlatitudes. In the tropics, the model amplitude of the near-tropopause annual cycle is weak. This is likely due to the annual amplitude of mean vertical upwelling near the tropopause, which analysis suggests is ~30% weaker than in the real atmosphere.

scholarly journals An integrated analysis of contemporary methane emissions and concentration trends over China using in situ, satellite observations, and model simulations

2021 ◽  
Author(s):  
Haiyue Tan ◽  
Lin Zhang ◽  
Xiao Lu ◽  
Yuanhong Zhao ◽  
Bo Yao ◽  
...  
Keyword(s):  
Model Simulation ◽  
Eastern China ◽  
Recent Decade ◽  
Satellite Observations ◽  
Integrated Analysis ◽  
Mixing Ratio ◽  
Emission Mitigation ◽  
Model Simulations ◽  
Ch4 Emissions ◽  
Mixing Ratios

Abstract. China, being one of the major emitters of greenhouse gases, has taken strong actions to tackle climate change, e.g., to achieve carbon neutrality by 2060. It also becomes important to better understand the changes in the atmospheric mixing ratio and emissions of CH4, the second most important human-influenced greenhouse gas, in China. Here we analyze the sources contributing to the atmospheric CH4 mixing ratio and their trends in China over 2007–2018 using the GEOS-Chem model simulations driven by two commonly used global anthropogenic emission inventories: the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2) and the Community Emissions Data System (CEDS). The model results are interpreted with an ensemble of surface, aircraft, and satellite observations of CH4 mixing ratios over China and the Pacific region. The EDGAR and CEDS estimates show considerable differences reflecting large uncertainties in estimates of Chinese CH4 emissions. Chinese CH4 emission estimates based on EDGAR and natural sources increase from 46.7 Tg per annum (Tg a−1) in 1980 to 69.8 Tg a−1 in 2012 with an increase rate of 0.7 Tg a−2, and estimates with CEDS increase from 32.9 Tg a−1 in 1980 and 76.7 Tg a−1 in 2014 (a much stronger trend of 1.3 Tg a−2 over the period). Both surface, aircraft, and satellite measurements indicate CH4 increase rates of 7.0–8.4 ppbv a−1 over China in the recent decade. We find that the model simulation using the CEDS inventory and interannually varying OH levels can best reproduce these observed CH4 mixing ratios and trends over China. Model results over China are sensitive to the global OH level, with a 10 % increase in the global tropospheric volume-weighted mean OH concentration presenting a similar effect to that of a 47 Tg a−1 decrease in global CH4 emissions. We further apply a tagged tracer simulation to quantify the source contributions from different emission sectors and regions. We find that domestic CH4 emissions account for 11.4 % of the mean surface mixing ratio and drive 68.3 % of the surface trend (mainly via the energy sector) in China over 2007–2018. We emphasize that intensive CH4 measurements covering eastern China will help better assess the driving factors of CH4 mixing ratios and support the emission mitigation in China.

scholarly journals Methane plume over South Asia during the monsoon season: satellite observation and model simulation

2008 ◽  
Vol 8 (4) ◽  
pp. 13453-13478 ◽  
Author(s):  
X. Xiong ◽  
S. Houweling ◽  
J. Wei ◽  
E. Maddy ◽  
F. Sun ◽  
...  
Keyword(s):  
South Asia ◽  
Transport Process ◽  
Model Simulation ◽  
Monsoon Season ◽  
Satellite Observation ◽  
Satellite Observations ◽  
Atmospheric Pollutants ◽  
Local Surface ◽  
Atmospheric Infrared Sounder ◽  
Upper Troposphere

Abstract. Satellite observations of methane (CH4) using the Atmospheric Infrared Sounder (AIRS) on the EOS/Aqua platform from 2003–2007 demonstrate a strong, plume-like enhancement of CH4 in the middle to upper troposphere over the South Asia during July, August and September, and its maximum occurs in early September. Simulations using the global tracer model version 3 (TM3) also show similar seasonal enhancement of CH4 in the same region. The model results also suggest that this enhancement is associated with transport process and local surface emissions, thus the observations to tropospheric CH4during the monsoon season may be used to constrain the models for a better estimation of Asian CH4 sources. Further comparisons between AIRS observations and the model simulations indicate a possible overestimate of CH4 emissions from rice paddies in Southeast Asia. Moreover, the observed tropospheric CH4 enhancement from AIRS provides evidence for the strong transport of atmospheric pollutants from the lower to the upper troposphere in Asia during the monsoon season, and the observed rapid disappearance of local CH4 maximum in September may provide valuable information for studying the dissipation of the Tibetan anticyclone and the withdrawal of monsoon.

scholarly journals On the performance of satellite-based observations of <i>CO</i><sub>2</sub> in capturing the NOAA Carbon Tracker model and ground-based flask observations over Africa land mass

2019 ◽  
Author(s):  
Anteneh Getachew Mengistu ◽  
Gizaw Mengistu Tsidu
Keyword(s):  
Model Simulation ◽  
Satellite Observation ◽  
Satellite Observations ◽  
Lower Altitude ◽  
Equatorial Africa ◽  
In Situ Observations ◽  
The Mean ◽  
Data Gap ◽  
Good Agreement

Abstract. Africa is one of the most data-scarce regions as satellite observation at the equator is limited by cloud cover and there are a very limited number of ground-based measurements. As a result, the use of simulations from models are mandatory to fill this data gap. A comparison of satellite observation with model and available in-situ observations will be useful to estimate the performance of satellites in the region. In this study, GOSAT XCO2 is compared with the NOAA CT2016 and six flask observations over Africa using five years of data covering the period from May 2009 to April 2014. Ditto for OCO-2 XCO2 against NOAA CT16NRT17 and eight flask observations over Africa using two years of data covering the period from January 2015 to December 2016. The analysis shows that the XCO2 from GOSAT is higher than XCO2 simulated by CT2016 by 0.28 ppm whereas OCO-2 XCO2 is lower than CT16NRT17 by 0.34 ppm on African landmass on average. The mean correlations of 0.83 and 0.60 and average RMSD of 2.30 and 2.57 ppm are found between the model and the respective datasets from GOSAT and OCO-2 implying the existence of a reasonably good agreement between CT and the two satellites over Africa's land region. However, significant variations were observed in some regions. For example, OCO-2 XCO2 are lower than that of CT16NRT17 by up to 3 ppm over some regions in North Africa (e.g., Egypt, Libya, and Mali) whereas it exceeds CT16NRT17 XCO2 by 2 ppm over Equatorial Africa (10° S–10° N). This regional difference is also noted in the comparison of model simulations and satellite observations with flask observations over the continent. For example, CT shows a better sensitivity in capturing flask observations over sites located in Northern Africa. In contrast, satellite observations have better sensitivity in capturing flask observations in lower altitude island sites. CT2016 shows a high spatial mean of seasonal mean RMSD of 1.91 ppm during DJF with respect to GOSAT while CT16NRT17 shows 1.75 ppm during MAM with respect to OCO-2. On the other hand, low RMSD of 1.00 and 1.07 ppm during SON in the model XCO2 with respect to GOSAT and OCO-2 are determined respectively indicating better agreement during autumn. The model simulation and satellite observations exhibit similar seasonal cycles of XCO2 with a small discrepancy over Southern Africa and during wet seasons over all regions.

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