GCAP 2.0: a global 3-D chemical-transport model framework for past, present, and future climate scenarios

This paper describes version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version E2.1 of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). Meteorology for driving GEOS-Chem has been archived from the E2.1 contributions to phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the pre-industrial era and the recent past. In addition, meteorology is available for the near future and end of the century for seven future scenarios ranging from extreme mitigation to extreme warming. Emissions and boundary conditions have been prepared for input to GEOS-Chem that are consistent with the CMIP6 experimental design. The model meteorology, emissions, transport, and chemistry are evaluated in the recent past and found to be largely consistent with GEOS-Chem driven by the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) product and with observational constraints.

GCAP 2.0: A global 3-D chemical-transport model framework for past, present, and future climate scenarios

This manuscript describes version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version E2.1 of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). Meteorology for driving GEOS-Chem has been archived from the E2.1 contributions to Phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the preindustrial and recent past. In addition, meteorology is available for the near future and end-of-the century for seven future scenarios ranging from extreme mitigation to extreme warming. Emissions and boundary conditions have been prepared for input to GEOS-Chem that are consistent with the CMIP6 experimental design. The model meteorology, emissions, transport and chemistry are evaluated in the recent past and found to be largely consistent with GEOS-Chem driven by the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) product and with observational constraints.

The MJO-QBO Relationship in a GCM with Stratospheric Nudging

Observational studies show a strong connection between the intraseasonal Madden-Julian oscillation (MJO) and the stratospheric quasi-biennial oscillation (QBO): the boreal winter MJO is stronger, more predictable, and has different teleconnections when the QBO in the lower stratosphere is easterly versus westerly. Despite the strength of the observed connection, global climate models do not produce an MJO-QBO link. Here the authors use a current-generation ocean-atmosphere coupled NASA Goddard Institute for Space Studies global climate model (Model E2.1) to examine the MJO-QBO link. To represent the QBO with minimal bias, the model zonal mean stratospheric zonal and meridional winds are relaxed to reanalysis fields from 1980-2017. The model troposphere, including the MJO, is allowed to freely evolve. The model with stratospheric nudging captures QBO signals well, including QBO temperature anomalies. However, an ensemble of nudged simulations still lacks an MJO-QBO connection.

The interactive global fire module pyrE (v1.0)

Fires affect the composition of the atmosphere and Earth's radiation balance by emitting a suite of reactive gases and particles. An interactive fire module in an Earth system model (ESM) allows us to study the natural and anthropogenic drivers, feedbacks, and interactions of open fires. To do so, we have developed pyrE, the NASA GISS (Goddard Institute for Space Studies) interactive fire emissions module. The pyrE module is driven by environmental variables like flammability and cloud-to-ground lightning, calculated by the GISS ModelE ESM, and parameterized by anthropogenic impacts based on population density data. Fire emissions are generated from the flaming phase in pyrE (active fires). Using pyrE, we examine fire occurrence, regional fire suppression, burned area, fire emissions, and how it all affects atmospheric composition. To do so, we evaluate pyrE by comparing it to satellite-based datasets of fire count, burned area, fire emissions, and aerosol optical depth (AOD). We demonstrate pyrE's ability to simulate the daily and seasonal cycles of open fires and resulting emissions. Our results indicate that interactive fire emissions are biased low by 32 %–42 %, depending on emitted species, compared to the GFED4s (Global Fire Emissions Database) inventory. The bias in emissions drives underestimation in column densities, which is diluted by natural and anthropogenic emissions sources and production and loss mechanisms. Regionally, the resulting AOD of a simulation with interactive fire emissions is underestimated mostly over Indonesia compared to a simulation with GFED4s emissions and to MODIS AOD. In other parts of the world pyrE's performance in terms of AOD is marginal to a simulation with prescribed fire emissions.

Short-Lived Climate Forcers over the Arctic between 1995 and 2015 as simulated by the GISS modelE2.1

<p>The Arctic Monitoring and Assessment Programme (AMAP) is currently assessing the impacts of Short-Lived Climate Forcers (SLCF) on Arctic climate and air quality. In support of the assessment, we used the NASA Goddard Institute of Space Sciences (GISS) Earth System Model (modelE2.1), with prescribed sea surface temperature and sea-ice fraction, to simulate SLCF concentrations globally between 1995 and 2015. Two simulations were conducted, using the One-Moment Aerosol (OMA) and the Multiconfiguration Aerosol TRacker of mIXing state (MATRIX) aerosol modules. OMA is a mass-based scheme in which aerosols are assumed to remain externally mixed and have a prescribed and constant size distribution, while MATRIX is an aerosol microphysics scheme based on the quadrature method of moments, which is able to explicitly simulate the mixing state of aerosols. Anthropogenic emissions from the ECLIPSE v6b emissions database were used, along with emissions from aircrafts and open biomass burning from the Coupled Model Intercomparison Project Phase 6 (CMIP6), while the natural emissions of sea salt, DMS, isoprene and dust are calculated interactively. The simulated monthly surface concentrations of sulfate (SO<sub>4</sub>), black carbon (BC), organic carbon (OA), and ozone (O<sub>3</sub>) are compared with observations from a set of Arctic stations, extracted from the EBAS and IMPROVE databases, as well as a few additional locations. Simulated aerosol optical depths (AOD) are also compared with Advanced Very-High Resolution Radiometer (AVHRR). The study will present the evaluation of the modelE2.1 in simulating SLCF levels over the Arctic using different aerosol schemes, along with observed and simulated trends of SLCFs over the Arctic between 1995 and 2015.</p><div> <div> <div> </div> </div> </div>

The Response of the QBO to Increases in CO2 Using Three Atmospheric Chemistry Configurations

<p>Long-term projections of the Quasi-Biennial Oscillation (QBO) remain highly uncertain. This is partly due to the paucity of models which are able to properly simulate that phenomenon. Only 5 of the 47 CMIP5 models are capable of spontaneously generating a realistic QBO (Butchart et al., 2018), and even those models exhibit large biases in key QBO characteristics (e.g. amplitude, period, vertical extent) when compared with observations. Furthermore, only 1 of these 5 employed interactive atmospheric chemistry, which is known to modulate QBO dynamics.</p><p>We here investigate the QBO response to increased greenhouse gases using the NASA Goddard Institute for Space Studies Middle Atmosphere Model E2.2. Compared to lower vertical resolution versions of Model E, version 2.2 has a higher model top (0.002 hPa), and additional interactive non-orographic gravity wave drag sources from convection and shear, which produce a sufficiently realistic QBO, thus rendering it suitable for use in climate change studies. Steady-state responses to doubled and quadrupled CO<sub>2</sub><span> from </span>a pre-industrial control are analyzed, as well as the transient response to a 1% per year CO<sub>2</sub><span> </span>increase. In addition, we systematically explore the impact of interactive chemistry in modulating the QBO response to increased CO<sub>2</sub><span> by contrasting </span>interactive, prescribed, and linearized ozone chemistry configurations of the model. Overall, in response to increase CO<sub>2</sub> concentrations the QBO is seen to increase in frequency and weaken in amplitude, consistent with previous results, but the memory of the tropical stratosphere may complicate assessments of trends in chemistry and surface impacts. We also discuss implications for the trade-off between ensemble size and the complexity of the chemistry scheme in the model.</p>

Computational and Statistical Analysis of Surface Temperature over Inhambane-Mozambique from 1931-2015: The Future Implications

The danger of the El Nino southern oscillation (ENSO) over tropical pacific might be heading for an all-time high. Eighty-five years (1931-2015) surface temperature dataset from Goddard Institute for Space Studies (GISS) over Inhambane-Mozambique were used for this study. The dataset was analyzed using the computational and statistical technique. The maximum monthly surface temperature that was recorded within eighty-five years was given as 16 oC (January - 1990), 21.4 oC (February - 2006), 26.3 oC (March - 2010), 32.7 oC (April - 2010), 35.2 oC (May - 1978), 36.2 oC (June - 2012), 34.8 oC (July - 2002), 32.4 oC (August - 1987), 31.2 oC (September - 1987), 28.7 oC (October - 1951), 22.1 oC (November – 1977 & 2011) and 17.6 oC (December - 2013). From the study, it was discovered that droughts over Mozambique and parts of Southern Africa were not caused by certain extreme ENSO. Rather, the drought was caused by series of continuous processes (extreme weather conditions) that influence certain atmospheric conditions.

A General View of TOPSIS Method Involving Multi-Attribute Decision Making Problems

The TOPSIS method, commonly known as the technique for order performance by similarity to ideal solutions, is one of the most popular approaches used in the multi-attribute decision making (MADM). In this method has some advantages are simplicity, rationality, comprehensibility, good computational efficiency and ability to measure the relative performance for each alternative in a simple mathematical form. In the last four decades world is getting warmer. It is whether the cause of human activity or natural variability. The thermometer reading all round the world have risen steadily since the beginning of the industrial revolution. According to the ongoing temperature analysis conducted by scientist at NASA’s Goddard Institute for Space Studies (GISS), the average global temperature on the Earth has increased about 0.80 Celsius since 1880. So, applying this method to determines the best solution from a set of alternatives with certain attributes. The best alternative is chosen based on its Euclidean distance from the ideal solution. The aim of this paper to systematizes the knowledge within the scope of techniques of decision taking with the use of the TOPSIS method. Simple numerical examples that reference real situations show practical applications of different aspects of this method.

Contribution of SST change to multidecadal global and continental surface air temperature trends between 1910 and 2013

The global mean surface air temperature (GMST) shows multidecadal variability over the period of 1910–2013, with an increasing trend. This study quantifies the contribution of hemispheric surface air temperature (SAT) variations and individual ocean sea surface temperature (SST) changes to the GMST multidecadal variability for 1910–2013. At the hemispheric scale, both the Goddard Institute for Space Studies (GISS) observations and the Community Earth System Model (CESM) Community Atmosphere Model 5.3 (CAM5.3) simulation indicate that the Northern Hemisphere (NH) favors the GMST multidecadal trend during periods of accelerated warming (1910–1945, 1975–1998) and cooling (1940–1975, 2001–2013), whereas the Southern Hemisphere (SH) slows the intensity of both warming and cooling processes. The contribution of the NH SAT variation to the GMST multidecadal trend is higher than that of the SH. We conduct six experiments with different ocean SST forcing, and find that all the oceans make positive contributions to the GMST multidecadal trend during rapid warming periods. However, only the Indian, North Atlantic, and western Pacific oceans make positive contributions to the GMST multidecadal trend between 1940 and 1975, whereas only the tropical Pacific and the North Pacific SSTs contribute to the GMST multidecadal trend between 2001 and 2013. The North Atlantic and western Pacific oceans have important impacts on modulating the GMST multidecadal trend across the entire 20th century. Each ocean makes different contributions to the SAT multidecadal trend of different continents during different periods.