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At least 613 records · Page 34

Changes in the Structure and Propagation of the MJO with Increasing CO2

Changes in the Madden-Julian Oscillation (MJO) with increasing CO2 concentrations are examined using the Goddard Institute for Space Studies Global Climate Model (GCM). Four simulations performed with fixed CO2 concentrations of 0.5, 1, 2 and 4 times pre-industrial levels using the GCM coupled with a mixed layer ocean model are analyzed in terms of the basic state, rainfall and moisture variability, and the structure and propagation of the MJO.The GCM simulates basic state changes associated with increasing CO2 that are consistent with results from earlier studies: column water vapor increases at approximately 7.1% K(exp -1), precipitation also increases but at a lower rate (approximately 3% K(exp -1)), and column relative humidity shows little change. Moisture and rainfall variability intensify with warming. Total moisture and rainfall variability increases at a rate that is similar to that of the mean state change. The intensification is faster in the MJO-related anomalies than in the total anomalies, though the ratio of the MJO band variability to its westward counterpart increases at a much slower rate. On the basis of linear regression analysis and space-time spectral analysis, it is found that the MJO exhibits faster eastward propagation, faster westward energy dispersion, a larger zonal scale and deeper vertical structure in warmer climates.

Adames, Angel F.↗

Vertical Profiles of Mars 1.27 Micrometer O2 Dayglow from MRO CRISM Limb Spectra: Seasonal/global Behaviors, Comparisons to LMDGCM Simulations, and a Global Definition for Mars Water Vapor Profiles

Since July of 2009, The Compact Reconnaissance Imaging Spectral Mapper (CRISM) onboard the Mars Re- connaissance Orbiter (MRO) has periodically obtained pole-to-pole observations (i.e., full MRO orbits) of limb scanned visible/near IR spectra (lambda= 0.4 - 4.0 micrometers, delta lambda approx. 10 nm- Murchie et al., 2007). These CRISM limb observations support the first seasonally and spatially extensive set of Mars 1.27 micometers O2 (1 delta(sub g)) day-glow profile retrievals (approx. 1100) over greater than or equal to 8-80 km altitudes. Their comparison to Laboratoire de Meteorologie Dynamique (LMD) global climate model (GCM) simulated O2 (1 delta(sub g)) volume emission rate (VER) profiles, as a function of altitude, latitude, and season (solar longitude, L(sub s), supports several key conclusions regarding Mars atmospheric water vapor (which is derived from O2 (1 delta(sub g)) emission rates), Mars O3, and the collisional de-excitation of O2 (1 delta(sub g)) in the Mars CO2 atmosphere. Current (Navarro et al., 2014) LMDGCM simulations of Mars atmospheric water vapor fall 2-3 times below CRISM derived water vapor abundances at 20-40 km altitudes over low-to-mid latitudes in northern spring (L(sub s) = 30-60 deg), and northern mid-to-high latitudes over northern summer (L(sub s) = 60-140 deg). In contrast, LMDGCM simulated water vapor is 2-5 times greater than CRISM derived values at all latitudes and seasons above 40 km, within the aphelion cloud belt (ACB), and over high-southern to mid-southern latitudes in southern summer (L(sub s) = 190-340 deg) at 15-35 km altitudes. Overall, the solstitial summer-to-winter hemisphere gradients in water vapor are reversed between the LMDGCM modeled versus the CRISM derived water vapor abundances above 10-30 km altitudes. LMDGCM-CRISM differences in water vapor profiles correlate with LMDGCM-CRISM differences in cloud mixing profiles; and likely reflect limitations in simulating cloud microphysics and radiative forcing, both of which restrict meridional transport of water from summer- to-winter hemispheres on Mars (Clancy et al., 1996; Montmessin et al., 2004; Steele et al., 2014; Navarro et al., 2014) and depend on uncertain cloud microphysical properties (Navarro et al., 2014). The derived low-to-mid latitude changes in Mars water vapor vertical distributions should reduce current model- data disagreements in column O3 and H2O2 abundances over low-to-mid latitudes (e.g., within the ACB; Lefevre et al., 2008; Encrenaz et al., 2015; Clancy et al., 2016). Lastly, the global/seasonal average com- parison of CRISM and LMDGCM O2 (1 delta(sub g)) VER below 20 km altitudes indicates a factor of approx. 3 times lower value (0.25 x 10(exp -20) cu cm sec(exp -1)) for the CO2 collisional de-excitation rate coefficient of O2 (1 delta(sub g)) than derived recently by Guslyakova et al. (2016).

Clancy, R. Todd↗

Bringing Climate Scientist's Tools into Classrooms to Improve Conceptual Understandings

Efforts to address anthropogenic global climate change (AGCC) require public understanding of Earth and climate science. To meet this need, educational reforms and prominent scientists have called for instructional approaches that teach students how climate scientists examine AGCC. Yet, only a few educational studies have reported clear empirical results on what instructional approaches and climate education technologies best accomplish this goal. This manuscript presents detailed analysis and statistically significant results on the educational impact pre to post of students learning to use a National Aeronautics and Space Administration (NASA) global climate model (GCM). This series of case studies demonstrates that differing instructional approaches and climate education technologies result in differing levels of understanding of AGCC and ability to engage with policies addressing it. Students who learned the scientific process of climate modeling scored significantly higher pre to post on exams (quantitatively) and gained more complete conceptual understandings of the issue (qualitatively). Yet, teaching students to conduct research with complex technology can be difficult. This study also found lecture-based learning better improved recall of facts about GCMs tested by multiple-choice questions. Our findings indicate what educational systems and related technologies might provide the public with the conceptual understandings necessary to engage in the political debate over AGCC.

Public understanding↗

New York City Panel on Climate Change 2019 Report Chapter 5: Mapping Climate Risk

The mapping work of the NPCC is focused on illustrating spatial climate risk information to inform policy makers, stakeholders, and the public of the distribution of climate risk across the landscape of New York City. Flood risk, overall, has been the primary focus of climate risk, based on a variety of approaches including global climate models, semiempirical studies, literature surveys, expert opinion, and historic tide gauge and more recently, satellite observations of sea level rise. Maps of potential future flood extents are used to visualize coastal flooding extents at the neighborhood scale and to assess the progression of citywide flood risk throughout the 21st century. The NPCC maps were developed as a tool to illustrate our present understanding of the potential futures for which we need to prepare. This chapter reviews the background, methodology, and limitations of the NPCC3 (and NPCC2) mapping approach and features new citywide maps of mean sea level rise, monthly tidal flooding, and 100year return period flooding under a high end scenario of sea level rise. It concludes with a discussion of future mapping efforts and next steps that the NPCC could consider.

Patrick, Lesley↗

Searching for Life on Mars: The Contamination Paradox

As we search for life on Mars, we will be simultaneously contaminating Mars with life from Earth. The contamination from Earth could be mistaken for Martian life. How can this paradox be avoided? With the results of our research, the scientific community will be able to determine locations of future habitats that minimize the aerial extent subject to bio-contaminants, protect sites of astrobiological interest, and constrain landing site selection of life detection missions to reduce risk of false positives. We consider a putative human habitat on Mars. Biological contaminants will flow out of the habitat into the Martian atmosphere, and the atmosphere will move these contaminants around. How many biological particles per year will be released from the habitat into the Martian ambient environment? How far will the contamination travel? In what directions will it travel? How long will the contamination be in the atmosphere? We study these questions quantitatively by simulating the Martian atmosphere using the NASA Ames Mars Global Climate Model. Various combinations of human habitat locations and contaminant sizes are considered. The results from these simulations enable the creation of novel contamination heat maps showing the aerial distribution of contaminants from putative human habitats on Mars.

Contamination↗

Effect of Irrigation on Humid Heat Extremes

Most studies of irrigation as an anthropogenic climate forcing focus on its cooling effects. However, irrigation also increases humidity, and so may not ameliorate humid heat and its extremes. We analyzed global climate model results over hot locations and seasons at high temporal resolution to estimate the impact of irrigation on humid heat extremes, quantified as different percentiles of wet-bulb temperature (T(sub w)), under contemporary conditions. We found that although irrigation reduced temperature, the median and higher percentiles of T(sub w) on average did not decrease. Increases in T(sub w) percentile values and increases in frequency of dangerous T(sub w) of several days per year due to irrigation were found in some densely populated regions, including the central United States and the Middle East, while the Ganges basin saw reduced T(sub w). Changes in T(sub w) were partly associated with the differential regional impacts of irrigation on moisture transport. These results underline the importance of considering impacts of climate forcings on humidity as well as temperature in evaluating associated effects on heat extremes.

Irrigation↗

Midlatitude cyclone processes as a key to understanding climate sensitivity

Global climate models (GCMs) differ greatly in their shortwave cloud feedback. One feature that is consistent across GCMs is a positive shortwave cloud feedback in the subtropics, and a negative shortwave cloud feedback across the midlatitudes. Confidence has grown in the mechanisms that lead to, and the strength of, the subtropical shortwave cloud feedback, but the midlatitude negative shortwave cloud feedback is not well-constrained or well-understood. It is critical to reduce uncertainty in midlatitude shortwave cloud feedback. A more positive midlatitude shortwave cloud feedback in the sixth coupled model intercomparison project (CMIP6) has been found to be one of the primary causes of the increased climate sensitivity of CMIP6 models relative to CMIP5. We show that changes in midlatitude cyclones in future climates are the primary cause of the negative shortwave cloud feedback and are thus key to understanding the high climate sensitivity in the most recent GCMs. Warming-induced changes in cloud liquid water path in midlatitude cyclones can almost entirely be explained by Clausius-Clapeyron increasing moisture convergence into cyclones. One concern with simulating midlatitude cyclones is the lack of predictive skill at low resolution. A more realistic relationship between moisture flux and cyclone liquid content is found at high horizontal resolution (∆x<25km), but the cloud feedback within cyclones can be explained by increased moisture convergence across low- and high-resolution models. Observations and models agree that the extratropical shortwave cloud feedback is moderated by precipitation processes in cyclones. This rules out a large contribution from ice-to-liquid transitions, as has been hypothesized in previous studies. Understanding and constraining these precipitation processes is crucial to constraining the response of midlatitude cyclones to warming and by extension climate sensitivity.

Cyclones↗

Response of Surface Shortwave Cloud Radiative Effect to Greenhouse Gases and Aerosols and Its Impact on Summer Maximum Temperature

Shortwave cloud radiative effects (SWCREs), defined as the difference of the shortwave radiative flux between all-sky and clear-sky conditions at the surface, have been reported to play an important role in influencing the Earth's energy budget and temperature extremes. In this study, we employed a set of global climate models to examine the SWCRE responses to CO2, black carbon (BC) aerosols, and sulfate aerosols in boreal summer over the Northern Hemisphere. We found that CO2 causes positive SWCRE changes over most of the NH, and BC causes similar positive responses over North America, Europe, and eastern China but negative SWCRE over India and tropical Africa. When normalized by effective radiative forcing, the SWCRE from BC is roughly 3–5 times larger than that from CO2. SWCRE change is mainly due to cloud cover changes resulting from changes in relative humidity (RH) and, to a lesser extent, changes in cloud liquid water, circulation, dynamics, and stability. The SWCRE response to sulfate aerosols, however, is negligible compared to that for CO2 and BC because part of the radiation scattered by clouds under all-sky conditions will also be scattered by aerosols under clear-sky conditions. Using a multilinear regression model, it is found that mean daily maximum temperature (Tmax) increases by 0.15 and 0.13 K per watt per square meter (W m−2) increase in local SWCRE under the CO2 and BC experiment, respectively. When domain-averaged, the contribution of SWCRE change to summer mean Tmax changes was 10 %–30 % under CO2 forcing and 30 %–50 % under BC forcing, varying by region, which can have important implications for extreme climatic events and socioeconomic activities.

surface shortwave cloud radiative effect↗

Reconstructing Subgrid Cloud Variability Guided by CloudSat/CALIPSO Observations

Predicting realistic cloud subgrid variability remains a challenge for Global Climate Models (GCMs) even though it can play an important role for proper representation of processes pertaining to cloud microphysics, precipitation, and radiation, but also for comparisons with satellite observations which are of much higher resolution than model grids. The diagnostic approach of subgrid cloud variability is commonly handled by subcolumn cloud generators. For a specific GCM, one ideally wants the subgrid variability used for comparisons with satellite observations to be created by the same generator and with the same rules as the one used for model integration. With this in mind, we have embarked in an effort to test and improve cloud subcolumn generators appropriate for GCMs. For this purpose, we use cloud (hydrometeor) products from active observations by the CloudSat radar (CPR) and the CALIPSO lidar (CALIOP). Cloud products from active sensors while suffering significant sampling and coverage drawbacks have the advantage of resolving both horizontal and vertical variability. The main question is: given a profile of cloud condensate mean and variance, can we create a subgrid cloud field that is statistically similar to the observed subgrid cloud field? By “statistically”, we suggest that we do not aspire to reproduce “well” each individual subgrid cloud field of a GCM-scale region, but that our generator performs well for a large ensemble of cases. We simulate radar, passive imager, and radiation flux fields from the observed 2D cloud fields and create one-point statistics; we use the profiles of cloud condensate mean and variance as input to the generator to create subgrid cloud fields; we compare the statistics; we adjust the rules of the generator to create the best possible agreement between the radar, imager and radiation field statistics. In this process, the active observations have actually a dual role: they provide the actual subgrid cloud field which can be reduced to a profile of mean and variance used by the subcolumn generator, but they also provide the rules needed by the generator, such as measures (e.g, decorrelation length) of the vertical overlap of cloud fraction and of the condensate horizontal variability. This presentation will show our progress using Cloudsat and CALIPSO products in this dual fashion.

cloud↗

Reconstructing Subgrid Cloud Variability Guided by CloudSat/CALIPSO Observations

Predicting realistic cloud subgrid variability remains a challenge for Global Climate Models (GCMs) even though it can play an important role for proper representation of processes pertaining to cloud microphysics, precipitation, and radiation, but also for comparisons with satellite observations which are of much higher resolution than model grids. The diagnostic approach of subgrid cloud variability is commonly handled by subcolumn cloud generators. For a specific GCM, one ideally wants the subgrid variability used for comparisons with satellite observations to be created by the same generator and with the same rules as the one used for model integration. With this in mind, we have embarked in an effort to test and improve cloud subcolumn generators appropriate for GCMs. For this purpose, we use cloud (hydrometeor) products from active observations by the CloudSat radar (CPR) and the CALIPSO lidar (CALIOP). Cloud products from active sensors while suffering signi􀂦cant sampling and coverage drawbacks have the advantage of resolving both horizontal and vertical variability. The main question is: given a profile of cloud condensate mean and variance, can we create a subgrid cloud field that is statistically similar to the observed subgrid cloud field? By “statistically”, we suggest that we do not aspire to reproduce “well” each individual subgrid cloud field of a GCM-scale region, but that our generator performs well for a large ensemble of cases. We simulate radar, passive imager, and radiation flux fields from the observed 2D cloud fields and create one-point statistics; we use the profiles of cloud condensate mean and variance as input to the generator to create subgrid cloud fields; we compare the statistics; we adjust the rules of the generator to create the best possible agreement between the radar, imager and radiation field statistics. In this process, the active observations have actually a dual role: they provide the actual subgrid cloud field which can be reduced to a profile of mean and variance used by the subcolumn generator, but they also provide the rules needed by the generator, such as measures (e.g, decorrelation length) of the vertical overlap of cloud fraction and of the condensate horizontal variability. This presentation will show our progress using Cloudsat and CALIPSO products in this dual fashion.

clouds↗

Temperature and Chemical Species Distributions in the Middle Atmosphere Observed during Titan's Late Northern Spring to Early Summer

We present a study of the seasonal evolution of Titan’s thermal field and distributions of haze, C2H2, C2H4, C2H6, CH3C2H, C3H8, C4H2, C6H6, HCN, and HC3N from March 2015 (Ls = 66°) to September 2017 (Ls = 93°) (i.e., from the last third of northern spring to early summer). We analyzed thermal emission of Titan’s atmosphere acquired by the Cassini Composite Infrared Spectrometer with limb and nadir geometry to retrieve the stratospheric and mesospheric temperature and mixing ratios pole-to-pole meridional cross sections from 5 mbar to 50 μbar (120–650 km). The southern stratopause varied in a complex way and showed a global temperature increase from 2015 to 2017 at high-southern latitudes. Stratospheric southern polar temperatures, which were observed to be as low as 120 K in early 2015 due to the polar night, showed a 30 K increase (at 0.5 mbar) from March 2015 to May 2017 due to adiabatic heating in the subsiding branch of the global overturning circulation. All photochemical compounds were enriched at the south pole by this subsidence. Polar cross sections of these enhanced species, which are good tracers of the global dynamics, highlighted changes in the structure of the southern polar vortex. These high enhancements combined with the unusually low temperatures (<120 K) of the deep stratosphere resulted in condensation at the south pole between 0.1 and 0.03 mbar (240–280 km) of HCN, HC3N, C6H6 and possibly C4H2 in March 2015 (Ls = 66°). These molecules were observed to condense deeper with increasing distance from the south pole. At high-northern latitudes, stratospheric enrichments remaining from the winter were observed below 300 km between 2015 and May 2017 (Ls = 90°) for all chemical compounds and up to September 2017 (Ls = 93°) for C2H2, C2H4, CH3C2H, C3H8, and C4H2. In September 2017, these local enhancements were less pronounced than earlier for C2H2, C4H2, CH3C2H, HC3N, and HCN, and were no longer observed for C2H6 and C6 H6, which suggests a change in the northern polar dynamics near the summer solstice. These enhancements observed during the entire spring may be due to confinement of this enriched air by a small remaining winter circulation cell that persisted in the low stratosphere up to the northern summer solstice, according to predictions of the Institut Pierre Simon Laplace Titan Global Climate Model (IPSL Titan GCM). In the mesosphere we derived a depleted layer in C2H2, HCN, and C2H6 from the north pole to mid-southern latitudes, while C4H2, C3H4, C2H4, and HC3N seem to have been enriched in the same region. In the deep stratosphere, all molecules except C2H4 were depleted due to their condensation sink located deeper than 5 mbar outside the southern polar vortex. HCN, C4H2, and CH3C2H volume mixing ratio cross section contours showed steep slopes near the mid-latitudes or close to the equator, which can be explained by upwelling air in this region. Upwelling is also supported by the cross section of the C2H4 (the only molecule not condensing among those studied here) volume mixing ratio observed in the northern hemisphere. We derived the zonal wind velocity up to mesospheric levels from the retrieved thermal field. We show that zonal winds were faster and more confined around the south pole in 2015 (Ls = 67−72°) than later. In 2016, the polar zonal wind speed decreased while the fastest winds had migrated toward low-southern latitudes.

S Vinatier↗

Detectability of Molecular Signatures on TRAPPIST-1e through Transmission Spectroscopy Simulated for Future Space-based Observatories

Discoveries of terrestrial, Earth-sized exoplanets that lie within the habitable zone(HZ)of their host stars continu eto occur at increasing rates. Transit spectroscopy can potentially enable the detection of molecular signatures fromsuch worlds, providing an indication of the presence of an atmosphere and its chemical composition, includinggases potentially indicative of a biosphere. Such planets around nearby M-dwarf stars—such as TRAPPIST-1—provide a relatively good signal, high signal-to-noise ratio, and frequent transits for follow-up spectroscopy.However, even with these advantages, transit spectroscopy of terrestrial planets in the HZ of nearby M-stars willstill be a challenge. Herein, we examine the potential for future space observatories to conduct such observations,using a global climate model, a photochemical model, and a radiative transfer suite to simulate modern-Earth-likeatmospheric boundary conditions on TRAPPIST-1e. The detectability of biosignatures on such an atmosphere viatransmission spectroscopy is modeled for various instruments of the James Webb Space Telescope, Large UV/Optical/Infrared Surveyor, Habitable Exoplanet Observatory, and Origins. We show that only CO2at 4.3μm would be detectable at the>5σlevel in transmission spectroscopy, when clouds are included in our simulations.This is because the impact of clouds on scale height strongly limits the detectability of molecules in the atmosphere. Synergies between space- and ground-based spectroscopy may be essential in order to overcome these difficulties.

Daria Pidhorodetska↗

The Past and Future Changes in Climate of the Rice-Wheat Cropping Zone in Punjab, Pakistan

Agriculture is ranked top among Pakistan economic sectors vulnerable to the potential impacts of climate change. The agricultural production system is directly affected by weather inputs (temperature, solar radiation, and rainfall) that are projected to change in future (following increases in carbon dioxide and other greenhouse gasses). Although Climatic extremes such as drought, floods and heat waves, are expected to increase with detrimental consequences for agriculture and livestock production, yet changes in mean climates also pose challenges to sustainable development. This study presents climate change results for five districts within the major rice-wheat productivity zone of Punjab province in Pakistan. The results are focused on RCP8.5 mid-century (2040-2069) scenarios derived from five global climate models (GCMs) output and the Kharif (June-October) and Rabi (November-April) seasons. Analysis of recent historical weather data of Sialkot and Sheikhupura districts shows an increase in minimum temperatures and maximum temperatures and a large variation in rainfall. This temperature change and variability in rainfall are expected to enhance further as we approach 2050s. The mean maximum temperature is projected to increase by 2-2.5 ºC during the rice growing (Kharif) season and 2.4-2.7ºC during the wheat growing (Rabi) season. Rainfall during the rice growing season is more uncertain, with projections indicating an increase of 25%-35 % in the study region, while a minimal change is expected during the Rabi season. Climax of the rice growing season corresponds with the projected increase in monsoon intensity, leaving no doubt about the crop water demand satisfaction. However, a simultaneous increase in the day and night temperature may affect the growth and development of some critical phenological stages and thus could impact final yield.

Climate Change↗

Features and Characteristics of the New NASA MicroPuLse NETwork (MPLNET) Automatic Rain Detection Algorithm

The water cycle strongly influences life on Earth. In particular, the precipitation modifies the atmospheric column thermodynamics through the process of evaporation and serves as a proxy for latent heat modulation. For this reason, a correct precipitation parameterization (especially low-intensity precipitation) at global scale, bedsides improving our understanding of the hydrological cycle, it is crucial to reduce the associated uncertainty of the global climate models to correctly forecast future scenarios, i.e. to apply fast mitigation strategies. In this study we developed an algorithm to automatically detect precipitation from lidar measurements obtained by the National and Aeronautics Space Administration (NASA) Micropulse lidar network (MPLNET) permanent observational site in Goddard. The algorithm, once full operational, will deliver in Near Real Time (latency 1.5h) a new rain mask product that will be publicly available on MPLNET website as part of the new Version 3 Level 1.5 data. The methodology, based on an image processing technique, can detect only light precipitation events (defined by intensity and duration) as the morphological filters used through the detection process are applied on the lidar volume depolarization ratio range corrected composite images, i.e. heavy rain events are unusable as the lidar signal is completely extinguished after few meters in the precipitation or no signal detected because of the water accumulated on the receiver optics.

S. Lolli↗

Importance of Quantifying the Full-depth Carbon Reservoir of Jamaica Bay Salt Marshes, New York

Constraining uncertainty in the global carbon cycle requires valid assessment of both surface and stored carbon in marine and coastal ecosystems (Blue Carbon) as well as terrestrial carbon (forests, peatlands, and soils) [Pendleton et al., 2012]. Quantifying the global carbon stock of coastal salt marshes, potentially the most efficient carbon-burying ecosystems in the world per area, is a key area of further research in both of these fields Pendleton et al., 2012. One of the largest challenges is that despite the fact that salt marshes often sequester carbon several meters deep, nearly all estimates of salt marsh carbon stocks consider only the upper 1 m of sediment (Windham-Myers et al., 2015) [54]. This is particularly concerning because coastal wetlands are increasingly at risk due to climate change, sea level rise, and anthropogenic disturbance and destruction (Deegan et al., 2012) [15]. Using full-depth measurements from marsh cores, we estimate the carbon stock of five salt marshes in the highly urbanized estuary of Jamaica Bay, New York and argue that partial-depth measurements can underestimate carbon stocks. These estimates use calculated carbon content and probe depth data of these marshes collected between 2000 and 2019, applying this data across the full area of the marsh obtained from satellite imagery. Carbon density measurements are then multiplied by the full-depth volume of the marshes to create an estimate of total carbon stock. In addition to calculating present-day estimates, we compare our carbon stock estimates to historical Jamaica Bay imagery to calculate historical carbon stocks and carbon loss. The carbon stock estimates presented here show a 95% carbon stock loss between 1885 and 2019 in Jamaica Bay and highlight the severe underestimation of carbon stocks without full-depth calculations. These findings have important implications for disappearing salt marshes with regard to the global carbon cycle and the incorporation of belowground carbon into global climate models. The findings are increasingly relevant for advocacy efforts aiming to conserve these marshes with sea level rise.

Tidal wetlands↗

Extratropical Shortwave Cloud Feedbacks in the Context of the Global Circulation and Hydrological Cycle

Shortwave (SW) cloud feedback (SW FB ) is the primary driver of uncertainty in the effective climate sensitivity (ECS) predicted by global climate models (GCMs). ECS for several GCMs in the Sixth Coupled Model Intercomparison Project (CMIP6) exceed 5K, above the fifth assessment report (AR5) ‘likely’ maximum (4.5K) due to extratropical SW FB ’s that are more positive than those simulated in previous generation CMIP5 GCMs. Here we show that across 57 GCMs Southern Ocean SW FB can be predicted from the sensitivity of column-integrated liquid water mass LWP) to moisture convergence and to surface temperature. The response of LWP to moisture convergence and the response of albedo to LWP anti-correlate across GCMs. This is because GCMs that simulate a larger response of LWP to moisture convergence tend to have higher mean-state LWPs, which reduces the impact of additional LWP on albedo. Observational constraints suggest a modestly negative Southern Ocean SW FB — inconsistent with extreme ECS.

extratropical cloud response↗

Potential impacts of projected warming scenarios on winter wheat in the UK

The goals of this study are to analyse the impacts of 1.5 and 2.0°C scenarios on UK winter wheat using a combination of Global Climate Models (GCMs), crop models, planting dates and cultivars; to evaluate the impact of increased air temperature on winter wheat phenology and potential yield; to quantify the underlying uncertainties due to the multiple sources of variability introduced by climate scenarios, crop models and agronomic management. The data used to calibrate and evaluate three crop models were obtained from a field experiment with two irrigation amounts and two wheat cultivars that have different phenology and growth habit. After calibration, the model was applied to fifty locations across the wheat-growing area of the UK to cover all the main growing regions, with most points located in the main growing areas. Four GCMs, with two cultivars and five planting dates, were simulated at the end of the century. Results of this study showed that the UK potential wheat yield will increase by 2–8% under projected climate. Farmers will need to close such a gap in the future because it will have implications in terms of food security. Future climatic conditions might increase such a gap. Adaptation measures (e.g. moving the optimal planting time), along with climate-ready varieties bred for future conditions and with precision agriculture techniques can help to reduce this gap and ensure that the future actual UK wheat production will be close to the potential.

Climate change↗