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NASA NTRS2001

Soil Moisture and Snow Cover: Active or Passive Elements of Climate?

A key question in the study of the hydrologic cycle is the extent to which surface effects such as soil moisture and snow cover are simply passive elements or whether they can affect the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. GAPP region in determining the subsequent evolution of soil moisture and of snow cover. We have also made sensitivity studies with exaggerated soil moisture and snow cover anomalies in order to determine the physical processes that may be important. Results from simulations with realistic soil moisture anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. The initial state of soil moisture does not appear important, a result that held whether simulations were started in late winter or late spring. Model runs with exaggerated soil moisture reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in soil moisture, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and hence climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly affected the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectivity of snow is the most important process by which snow cover can impact climate, through lower surface temperatures and increased surface pressures. In early winter, the amount of solar radiation is very small and so this albedo, effect is inconsequential while in late winter, with the sun higher in the sky and period of daylight longer, the effect is much stronger. The results to date were obtained for model runs with present-day conditions. We are currently analyzing runs made with projected forcings for the 21st century to see if these results are modified in any way under likely scenarios of future climate change.

Oglesby, Robert J.↗

NASA NTRS2015

Combined Observational and Modeling Efforts to Better Understand Aerosol-Cloud-Precipitation Interactions Over Land: Preliminary Results from 7-SEAS/BASELInE 2013

This talk presents some of the detailed observations of low-level stratocumulus over northern Vietnam during 7-SEASBASELInE 2013 by SMARTLabs' ACHIEVE W-band cloud radar and other remote sensing instruments. These observations are the first of their kind for this region and will aid in ongoing studies of biomass-burning aerosol impacts on local and regional weather and climate. Preliminary results from simulations using the Goddard Cumulus Ensemble (GCE) with recently implemented triple-moment bulk microphysics to examine the sensitivity of low-level stratocumulus over land to aerosols are also presented. Recommendations for future observational activities in the 7-SEAS northern region in collaboration with international partners will also be discussed.

satellite remote sensing↗

NASA NTRS2016

Evaluation of Observed and Modelled Aerosol Lifetimes Using Radioactive Tracers of Opportunity and an Ensemble of 19 Global Models

Aerosols have important impacts on air quality and climate, but the processes affecting their removal from the atmosphere are not fully understood and are poorly constrained by observations. This makes modelled aerosol lifetimes uncertain. In this study, we make use of an observational constraint on aerosol lifetimes provided by radionuclide measurements and investigate the causes of differences within a set of global models. During the Fukushima Dai-Ichi nuclear power plant accident of March 2011, the radioactive isotopes cesium-137 (Cs-137) and xenon-133 (Xe-133) were released in large quantities. Cesium attached to particles in the ambient air, approximately according to their available aerosol surface area. Cs-137 size distribution measurements taken close to the power plant suggested that accumulation mode (AM) sulfate aerosols were the main carriers of cesium. Hence, Cs-137 can be used as a proxy tracer for the AM sulfate aerosol's fate in the atmosphere. In contrast, the noble gas Xe-133 behaves almost like a passive transport tracer. Global surface measurements of the two radioactive isotopes taken over several months after the release allow the derivation of a lifetime of the carrier aerosol. We compare this to the lifetimes simulated by 19 different atmospheric transport models initialized with identical emissions of Cs-137that were assigned to an aerosol tracer with each model's default properties of AM sulfate, and Xe-133 emissions that were assigned to a passive tracer. We investigate to what extent the modelled sulfate tracer can reproduce the measurements, especially with respect to the observed loss of aerosol mass with time. Modelled Cs-137and Xe-133 concentrations sampled at the same location and times as station measurements allow a direct comparison between measured and modelled aerosol lifetime. The e-folding lifetime e, calculated from station measurement data taken between 2 and 9 weeks after the start of the emissions, is 14.3 days (95% confidence interval 13.1-15.7 days). The equivalent modelled e lifetimes have a large spread, varying between 4.8 and 26.7 days with a model median of 9.42.3 days, indicating too fast a removal in most models. Because sufficient measurement data were only available from about 2 weeks after the release, the estimated lifetimes apply to aerosols that have undergone long-range transport, i.e. not for freshly emitted aerosol. However, modelled instantaneous lifetimes show that the initial removal in the first 2 weeks was quicker (lifetimes between 1 and 5 days) due to the emissions occurring at low altitudes and co-location of the fresh plume with strong precipitation. Deviations between measured and modelled aerosol lifetimes are largest for the northernmost stations and at later time periods, suggesting that models do not transport enough of the aerosol towards the Arctic. The models underestimate passive tracer (Xe-133) concentrations in the Arctic as well but to a smaller extent than for the aerosol (Cs-137) tracer. This indicates that in addition to too fast an aerosol removal in the models, errors in simulated atmospheric transport towards the Arctic in most models also contribute to the underestimation of the Arctic aerosol concentrations.

Radioactive isotopes↗

NASA NTRS2021

Summertime Transport Pathways from Different Northern Hemisphere Regions into the Arctic

Trace gases and aerosols play an important role in Arctic chemistry and climate. As most Arctic tracers and aerosols are transported from midlatitude source regions, long-range transport into the Arctic is one of the key factors to understand the current and future states of Arctic climate. While previous studies have investigated the airmass fraction and transit time distribution in the Arctic, the actual transport pathways and their underlying dynamics and efficiencies are yet to be understood. In this study, we implement a large ensemble of idealized tagged pulse passive tracers in the Whole Atmosphere Community Climate Model version 5 to identify and analyze summertime transport pathways from different Northern Hemisphere surface regions into the Arctic. Three different transport pathways are identified as those associated with fast, intermediate and slow time scales. Midlatitude tracers can be transported into the Arctic in the troposphere via the fast transport pathway (~8 days), which moves tracers northward from the source region mainly through transient eddies. For the intermediate transport pathway, which happens on 1~3 weeks’ time scales, midlatitude tracers are first zonally transported by the jet stream, and then advected northward into the Arctic over Alaska and northern North Atlantic. Tropical and subtropical tracers are transported into the Arctic lower stratosphere via the slow transport pathway (1~3 months), as the tracers are lifted upward into the tropical and subtropical lower stratosphere, and then transported into the Arctic following the isentropic surfaces.

Trace gases↗

NASA NTRS2023

The Impact of ENSO and NAO Initial Conditions and Anomalies on the Modeled Response to Pinatubo-Sized Volcanic Forcing

Strong, strato-volcanic eruptions are a substantial, intermittent source of natural climate variability. Initial atmospheric and oceanic conditions, such as El Niño Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO), also naturally impact climate on interannual timescales. We examine how initial conditions of ENSO and NAO contribute to the evolution of climate in the period following a Pinatubo-type eruption using a large (81-member) ensemble of model simulations in GISS model E2.1-G. Simulations are initialized from sampled conditions of ENSO and NAO using the protocol of the coordinated CMIP6 Volcanic Model Intercomparison Project (VolMIP) – where aerosols are forced with respect to time, latitude, and height. We analyze paired anomalous variations (perturbed – control) to understand changes in global and regional climate responses under positive, negative, and neutral ENSO and NAO conditions. In particular, we find that for paired anomalies there is a high probability of strong (∼1.5 °C) warming of northern Eurasia surface air temperature in the first winter after the volcanic eruption for negative NAO ensembles coincident with decreased lower stratospheric temperature at the poles, decreased geopotential height, and strengthening of the stratospheric polar vortex. Climate anomalies (relative to average conditions across the control period), however, show no mean warming and suggest that the strength of this response is impacted by conditions present in the selected period of the control run. Again using paired anomalies, we also observe that under both +ENSO and −ENSO ensembles sea surface temperature decreases in the first post-eruptive boreal winter coinciding with surface cooling from volcanic aerosols. Neutral ENSO ensembles, on the other hand, show variability in their response with no clear trend in post-eruptive warming or cooling. In general, paired anomalies from unperturbed simulations give insight into the evolution of the climate response to volcanic forcing; however, when compared with anomalies from climatological conditions, it is clear that paired anomalies are significantly affected by sampled initial conditions occurring at the time of the volcanic eruption.

volcanic eruptions↗

NASA NTRS2012

NASA Center for Climate Simulation (NCCS) Presentation

The NASA Center for Climate Simulation (NCCS) offers integrated supercomputing, visualization, and data interaction technologies to enhance NASA's weather and climate prediction capabilities. It serves hundreds of users at NASA Goddard Space Flight Center, as well as other NASA centers, laboratories, and universities across the US. Over the past year, NCCS has continued expanding its data-centric computing environment to meet the increasingly data-intensive challenges of climate science. We doubled our Discover supercomputer's peak performance to more than 800 teraflops by adding 7,680 Intel Xeon Sandy Bridge processor-cores and most recently 240 Intel Xeon Phi Many Integrated Core (MIG) co-processors. A supercomputing-class analysis system named Dali gives users rapid access to their data on Discover and high-performance software including the Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT), with interfaces from user desktops and a 17- by 6-foot visualization wall. NCCS also is exploring highly efficient climate data services and management with a new MapReduce/Hadoop cluster while augmenting its data distribution to the science community. Using NCCS resources, NASA completed its modeling contributions to the Intergovernmental Panel on Climate Change (IPCG) Fifth Assessment Report this summer as part of the ongoing Coupled Modellntercomparison Project Phase 5 (CMIP5). Ensembles of simulations run on Discover reached back to the year 1000 to test model accuracy and projected climate change through the year 2300 based on four different scenarios of greenhouse gases, aerosols, and land use. The data resulting from several thousand IPCC/CMIP5 simulations, as well as a variety of other simulation, reanalysis, and observationdatasets, are available to scientists and decision makers through an enhanced NCCS Earth System Grid Federation Gateway. Worldwide downloads have totaled over 110 terabytes of data.

Webster, William P.↗

NASA NTRS2015

Enhanced Weathering Strategies for Stabilizing Climate and Averting Ocean Acidification

Chemical breakdown of rocks, weathering, is an important but very slow part of the carbon cycle that ultimately leads to CO2 being locked up in carbonates on the ocean floor. Artificial acceleration of this carbon sink via distribution of pulverized silicate rocks across terrestrial landscapes may help offset anthropogenic CO2 emissions. We show that idealized enhanced weathering scenarios over less than a third of tropical land could cause significant drawdown of atmospheric CO2 and ameliorate ocean acidification by 2100. Global carbon cycle modelling driven by ensemble Representative Concentration Pathway (RCP) projections of twenty-first-century climate change (RCP8.5, business-as-usual; RCP4.5, medium-level mitigation) indicates that enhanced weathering could lower atmospheric CO2 by 30-300 ppm by 2100, depending mainly on silicate rock application rate (1 kg or 5 kg m(exp -2) yr (exp -1)) and composition. At the higher application rate, end-of-century ocean acidification is reversed under RCP4.5 and reduced by about two-thirds under RCP8.5. Additionally, surface ocean aragonite saturation state, a key control on coral calcification rates, is maintained above 3.5 throughout the low latitudes, thereby helping maintain the viability of tropical coral reef ecosystems. However, we highlight major issues of cost, social acceptability, and potential unanticipated consequences that will limit utilization and emphasize the need for urgent efforts to phase down fossil fuel emissions.

Taylor, Lyla L.↗

NASA NTRS2015

Enhanced Weathering Strategies for Stabilizing Climate and Averting Ocean Acidification - Supplementary Information

Chemical breakdown of rocks, weathering, is an important but very slow part of the carbon cycle that ultimately leads to CO2 being locked up in carbonates on the ocean floor. Artificial acceleration of this carbon sink via distribution of pulverized silicate rocks across terrestrial landscapes may help offset anthropogenic CO2 emissions. We show that idealized enhanced weathering scenarios over less than a third of tropical land could cause significant drawdown of atmospheric CO2 and ameliorate ocean acidification by 2100. Global carbon cycle modelling driven by ensemble Representative Concentration Pathway (RCP) projections of twenty-first-century climate change (RCP8.5, business-as-usual; RCP4.5, medium-level mitigation) indicates that enhanced weathering could lower atmospheric CO2 by 30-300 ppm by 2100, depending mainly on silicate rock application rate (1 kg or 5 kg m(exp. -2) yr (exp -1)) and composition. At the higher application rate, end-of-century ocean acidification is reversed under RCP4.5 and reduced by about two-thirds under RCP8.5. Additionally, surface ocean aragonite saturation state, a key control on coral calcification rates, is maintained above 3.5 throughout the low latitudes, thereby helping maintain the viability of tropical coral reef ecosystems. However, we highlight major issues of cost, social acceptability, and potential unanticipated consequences that will limit utilization and emphasize the need for urgent efforts to phase down fossil fuel emissions.

Taylor, Lyla L.↗

NASA NTRS2016

Global Ocean Evaporation Increases Since 1960 in Climate Reanalyses: How Accurate Are They?

AGCMs w/ Specified SSTs (AMIPs) GEOS-5, ERA-20CM Ensembles Incorporate best historical estimates of SST, sea ice, radiative forcing Atmospheric "weather noise" is inconsistent with specified SST. Instantaneous Sfc fluxes can be wrong sign (e.g. Indian Ocean Monsoon, high latitude oceans). Averaging over ensemble members helps isolate SST-forced signal. Reduced Observational Reanalyses: NOAA 20CR V2C, ERA-20C, JRA-55C Incorporate observed Sfc Press (20CR), Marine Winds (ERA-20C) and rawinsondes (JRA-55C) to recover much of true synoptic or weather w/o shock of new sat obs. Comprehensive Reanalyses (MERRA-2) Full suite of observational constraints- both conventional and remote sensing. But... substantial uncertainties owing to evolving satellite observing system. Multi-source Statistically Blended OAFlux, LargeYeager Blend reanalysis, satellite, and ocean buoy information. While climatological biases are removed, non-physical trends or variations in components remain. Satellite Retrievals GSSTF3, SeaFlux, HOAPS3... Global coverage. Retrieved near sfc wind speed, & humidity used with SST to drive accurate bulk aerodynamic flux estimates. Satellite inter-calibration, spacecraft pointing variations crucial. Short record ( late 1987-present). In situ Measurements ICOADS, IVAD, Res Cruises VOS and buoys offer direct measurements. Sparse data coverage (esp south of 30S. Changes in measurement techniques (e.g. shipboard anemometer height).

Climate↗

NASA NTRS2014

The Effects of Interactive Stratospheric Chemistry on Antarctic and Southern Ocean Climate Change in an AOGCM

Stratospheric ozone depletion has played a dominant role in driving Antarctic climate change in the last decades. In order to capture the stratospheric ozone forcing, many coupled atmosphere-ocean general circulation models (AOGCMs) prescribe the Antarctic ozone hole using monthly and zonally averaged ozone field. However, the prescribed ozone hole has a high ozone bias and lacks zonal asymmetry. The impacts of these biases on model simulations, particularly on Southern Ocean and the Antarctic sea ice, are not well understood. The purpose of this study is to determine the effects of using interactive stratospheric chemistry instead of prescribed ozone on Antarctic and Southern Ocean climate change in an AOGCM. We compare two sets of ensemble simulations for the 1960-2010 period using different versions of the Goddard Earth Observing System 5 - AOGCM: one with interactive stratospheric chemistry, and the other with prescribed monthly and zonally averaged ozone and 6 other stratospheric radiative species calculated from the interactive chemistry simulations. Consistent with previous studies using prescribed sea surface temperatures and sea ice concentrations, the interactive chemistry runs simulate a deeper Antarctic ozone hole and consistently larger changes in surface pressure and winds than the prescribed ozone runs. The use of a coupled atmosphere-ocean model in this study enables us to determine the impact of these surface changes on Southern Ocean circulation and Antarctic sea ice. The larger surface wind trends in the interactive chemistry case lead to larger Southern Ocean circulation trends with stronger changes in northerly and westerly surface flow near the Antarctica continent and stronger upwelling near 60S. Using interactive chemistry also simulates a larger decrease of sea ice concentrations. Our results highlight the importance of using interactive chemistry in order to correctly capture the influences of stratospheric ozone depletion on climate change over Antarctic and the Southern Ocean.

Antarctic climate change↗

NASA NTRSDate not supplied

A NASA GISTEMP Observational Uncertainty Ensemble: Regional and Monthly Uncertainty

The historical global temperature record is an essential data product for quantifying the variability and change of the Earth system. In recent years, better characterization of observational uncertainty in global and hemispheric trends has become available, but the methodologies are not necessarily applicable to analyses at smaller regional areas, or monthly means, where station sparsity and other systematic issues contribute to greater uncertainty. This work details a gridded uncertainty ensemble of historical temperature anomalies from the Goddard Institute for Space Studies (GISS) Surface Temperature product (GISTEMP) product. This ensemble characterizes the complex spatial and temporal correlation structure of uncertainty in gridded historical temperature, enabling proper uncertainty propagation for climate and social science at regional and monthly scales. This work details the methodology for generating the uncertainty ensemble, key statistics of the uncertainty evolution over space and time, and provides best practices for using the uncertainty ensemble in future studies. Summary statistics from the uncertainty ensemble are in good agreement with production GISTEMP. Two applications of the uncertainty ensemble are also presented. First, the warmest year on record is shown to most likely be 2016 with a 53.2% chance and 2020 as the second most likely with a 44.4% chance. Second, it is shown that the arctic is warming 2.5 - 5 times faster than the globe, significantly faster than the regularly quoted twice as fast.

GISTEMP↗

NASA NTRS2018

Climates of Warm Earth-Like Planets. I. 3D Model Simulations

We present a large ensemble of simulations of an Earth-like world with increasing insolation and rotation rate. Unlike previous work utilizing idealized aquaplanet congurations we focus our simulations on modern Earth-like topography. The orbital period is the same as modern Earth, but with zero obliquity and eccentricity. The atmosphere is 1 bar N2-dominated with CO2=400 ppmv and CH4=1 ppmv. The simulations include two types of oceans; one without ocean heat transport (OHT) between grid cells as has been commonly used in the exoplanet literature, while the other is a fully coupled dynamic bathtub type ocean. The dynamical regime transitions that occur as day length increases induce climate feedbacks producing cooler temperatures, rst via the reduction of water vapor with increasing rotation period despite decreasing shortwave cooling by clouds, and then via decreasing water vapor and increasing shortwave cloud cooling, except at the highest insolations. Simulations without OHT are more sensitive to insolation changes for fast rotations while slower rotations are relatively insensitive to ocean choice. OHT runs with faster rotations tend to be similar with gyres transporting heat poleward making them warmer than those without OHT. For slower rotations OHT is directed equator-ward and no high latitude gyres are apparent. Uncertainties in cloud parameterization preclude a precise determination of habitability but do not a affect robust aspects of exoplanet climate sensitivity. This is the first paper in a series that will investigate aspects of habitability in the simulations presented herein. The datasets from this study are open source and publicly available.

Planetary systems↗

NASA NTRS2020

Mechanisms Linked to Recent Ozone Decreases in the Northern Hemisphere Lower Stratosphere

Previous studies have robustly identified a decrease since 1998 in lower stratospheric (LS) ozone in the Northern Hemisphere (NH). While this ozone decrease is qualitatively explained as resulting from changes in the large‐scale circulation, there is not yet a quantitative mechanistic explanation of these changes. Here we explore the drivers of recent ozone changes using two different configurations of the Goddard Earth Observing System (GEOS) general circulation model. The first configuration of GEOS includes a full chemistry module and is constrained with meteorological fields from the Modern‐Era Retrospective analysis for Research and Applications, Version 2 (MERRA‐2). This configuration (M2GMI) is used to analyze an idealized tracer that covaries closely with ozone on interannual and decadal timescales, revealing that recent ozone decreases in the NH subtropics are associated with a poleward expansion of upwelling in the NH LS, with reduced (enhanced) downwelling over northern subtropics (midlatitudes). The second configuration of GEOS is a free‐running version of the GEOS Chemistry‐Climate Model (CCM) that is used to perform a ten‐member ensemble of free‐running simulations. Comparisons of the two configurations reveal that, while the free‐running model can produce negative ozone changes in the NH LS, the magnitude of these changes is significantly weaker, relative to both M2GMI and MERRA‐2; moreover, these weaker ozone decreases are consistent with weaker simulated changes in the residual circulation. Finally, we examine the GEOS model results in the broader context of the hindcast simulations performed as part of Phase 1 of the Chemistry Climate Modeling Initiative. We show that the majority of the free‐running simulations considered here also exhibit weaker long‐term residual circulation changes, compared to reanalyses.

Ozone↗

NASA NTRS2024

An Extensible Perturbed Parameter Ensemble for the Community Atmosphere Model Version 6

This paper documents the methodology and preliminary results from a Perturbed Parameter Ensemble (PPE) technique, where multiple parameters are varied simultaneously and the parameter values are determined with Latin hypercube sampling. This is done with the Community Atmosphere Model version 6 (CAM6), the atmospheric component of the Community Earth System Model version 2 (CESM2). We apply the PPE method to CESM2-CAM6 to understand climate sensitivity to atmospheric physics parameters. The initial simulations vary 45 parameters in the microphysics, convection, turbulence and aerosol schemes with 263 ensemble members. These atmospheric parameters are typically the most uncertain in many climate models. Control simulations are analyzed and targeted simulations to understand climate forcing due to aerosols and fast climate feedbacks. The use of various emulators is explored in the multi- dimensional space mapping input parameters to output metrics. Parameter impacts on various model outputs, such as radiation, cloud and aerosol properties are evaluated. Machine learning is also used to probe optimal parameter values against observations. Our findings show that using PPE is a valuable tool for climate uncertainty analysis. Furthermore, by varying many parameters simultaneously, we find that many different combinations of parameter values can produce results consistent with observations, and thus careful analysis of tuning is important. The CESM2-CAM6 PPE is publicly available, and extensible to other configurations to address questions of other model processes in the atmosphere and other model components (e.g. coupling to the land surface).

Machine learning↗

NASA NTRS2024

Celebrating 10 Years of the Sub-Seasonal to Seasonal Prediction Project and Looking to the Future

The conference clearly demonstrated the increasing interest and growth of the scientific community working on the development and application of sub-seasonal to seasonal prediction since the start of the World Weather Research Programme (WWRP)/World Climate Research Programme (WCRP) sub-seasonal to seasonal (S2S) prediction project in 2013. The conference, which was held at the University of Reading (United Kingdom), was organized into three main themes as briefly summarized below, with eleven invited talks, 74 oral contributed talks, and 101 posters. The conference also included a two-hour breakout session, wherein eight groups discussed the current state and prospect for S2S prediction, and an early career researcher event. A summary of these discussions and recommendations is presented below. The conference web page (https://research.reading.ac.uk/s2s-summit2023/) is archived at the University of Reading. Introductory comments by representatives of the World Meteorological Organization (WMO) WWRP and WCRP emphasized the importance of the weather–climate linkage, targeted by S2S forecasts (from 2 weeks to a season ahead), addressing the challenges of creating “end-to-end” forecasts that encompass the entire climate-services chain from the prediction science and forecast, to the development and issuing of forecast products tailored to informing user-decisions. They also emphasized the efficacy of multi-model ensemble efforts and databases to foster collaborations internationally and between operational centres and academia. Although the WWRP/WCRP S2S project comes to an end in 2023, S2S prediction will remain an important focus for WWRP and WCRP. In WWRP, a new project called SAGE (Sub-seasonal to seasonal predictions for Agriculture and Environment) will start in 2024. Another important legacy of the S2S project will be the maintenance of the S2S database (Vitart et al. 2017) and the establishment of a WMO Lead Center for sub-seasonal prediction multi-model ensemble (LC-SSPMME) which will provide real-time multi-model S2S climate information. In two keynote presentations, Prof. Brian Hoskins (University of Reading) and Dr. Gilbert Brunet (Australian Bureau of Meteorology) discussed the potential of S2S predictability and the ongoing journey for understanding and improving these predictions. This conference was a sequel to the International Conference on Sub-seasonal to Seasonal Prediction (Robertson et al., 2014) which took place in College Park (Maryland, USA) in February 2014 to celebrate the start of the WWRP/WCRP S2S project, and to WCRP and WWRP conferences in Boulder, USA, in 2018 (Merryfield et al., 2020). A significant development compared to the previous S2S conferences was the large number of presentations on research to operation (R2O) and S2S applications and on the use of artificial intelligence and machine learning (AI/ML) methods for S2S prediction. Some of these methods provide empirical S2S forecasts which are competitive with state-of-the-art dynamical models. Other presentations demonstrated that AI/ML can provide alternative calibration of dynamical model outputs to traditional methods. Several talks and posters highlighted the increasing use of AI/ML, including deep learning, in S2S forecast post-processing and using AI to identify higher flow-dependent skill. Finally, some presentations demonstrated the value of AI/ML methods for a better understanding of S2S sources of predictability and attribution of extreme events.

S. J. Woolnough↗

NASA NTRS2018

Impacts of Snow Darkening Effects by Light Absorbing Aerosols on Hydroclimate of Eurasia During Boreal Spring and Summer

In this study, we used the NASA GEOS-5 climate model to investigate the impact of snow darkening by light-absorbing aerosols on the hydro-climate if Eurasia during boreal spring and summer. Two sets of 10-member ensemble model integrations with prescribed sea surface temperature were carried out for 10 simulated years (2002-2011); one includes snow-darkening effects (SDE) by light-absorbing aerosols, and one does not (NSDE). Differences between the two experiments in the hydro-climates over Eurasia were evaluated. Results show that SDE warming is most pronounced during the melting season due to strong snow-albedo feedback in the vicinity of the retreating seasonal snowline. SDE spurs a Wet-First-Dry-Later (WFDL) modulation of the surface energy and water balances, characterized by an accelerated (days-to-weeks) snowmelt along with excessive runoff and a warming and wetting of the land during the early part of the melting season. The fast snowmelt is followed by a prolonged (> months) warming and desiccation of the land, stemming from a deficit of late-season snowmelt water and increased surface evaporation. The prolonged warming and drying of the land atmosphere system persist through the summer, sustained by atmospheric conditions favorable for the development of atmospheric blocking, i.e., higher mid-to-upper tropospheric geopotential height, lower relative humidity, reduced cloudiness and enhanced atmospheric subsidence. Overall, SDE by light absorbing aerosols leads to a warmer and drier boreal summer hydro-climate, increasing the frequency of the top 5% and 1% extreme hot days (as defined by NSDE statistics) over western and northern Eurasia by approximately three-fold and tenfold, respectively.

Snow darkening↗

NASA NTRS2021

Mid-Pliocene West African Monsoon Rainfall as Simulated in the PlioMIP2 Ensemble

The mid-Pliocene warm period (mPWP; ∼3.2 million years ago) is seen as the most recent time period characterized by a warm climate state, with similar to modern geography and ∼400 ppmv atmospheric CO2 concentration, and is therefore often considered an interesting analogue for near-future climate projections. Paleoenvironmental reconstructions indicate higher surface temperatures, decreasing tropical deserts, and a more humid climate in West Africa characterized by a strengthened West African Monsoon (WAM). Using model results from the second phase of the Pliocene Modelling Intercomparison Project (PlioMIP2) ensemble, we analyse changes of the WAM rainfall during the mPWP by comparing them with the control simulations for the pre-industrial period. The ensemble shows a robust increase in the summer rainfall over West Africa and the Sahara region, with an average increase of 2.5 mm/d, contrasted by a rainfall decrease over the equatorial Atlantic. An anomalous warming of the Sahara and deepening of the Saharan Heat Low, seen in >90 % of the models, leads to a strengthening of the WAM and an increased monsoonal flow into the continent. A similar warming of the Sahara is seen in future projections using both phase 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). Though previous studies of future projections indicate a west–east drying–wetting contrast over the Sahel, PlioMIP2 simulations indicate a uniform rainfall increase in that region in warm climates characterized by increasing greenhouse gas forcing. We note that this effect will further depend on the long-term response of the vegetation to the CO2 forcing.

Mid-Pliocene↗

NASA NTRS2003

Evidence for Limited Indirect Aerosol Forcing in Stratocumulus

Increases in cloud cover and condensed water contribute more than half of the indirect aerosol effect in an ensemble of general circulation model (GCM) simulations estimating the global radiative forcing of anthropogenic aerosols. We use detailed simulations of marine stratocumulus clouds and airborne observations of ship tracks to show that increases in cloud cover and condensed water in reality are far less than represented by the GCM ensemble. Our results offer an explanation for recent simplified inverse climate calculations indicating that indirect aerosol effects are greatly exaggerated in GCMs.

Ackerman, Andrew S.↗