Improving Madden–Julian Oscillation Simulation in Atmospheric General Circulation Models by Coupling with Snow–Ice–Thermocline One-dimensional Ocean Model

A one-column turbulent kinetic energy–type ocean mixed-layer model Snow–Ice–Thermocline (SIT) when coupled with three atmospheric general circulation models (AGCMs) to yielded superior Madden–Julian Oscillation (MJO) simulation. SIT is designed to have fine layers similar to those observed near the ocean surface and therefore can realistically simulate the diurnal warm layer and cool skin. This refined discretization of the near ocean surface in SIT provides accurate sea surface temperature (SST) simulation, thus facilitating realistic air–sea interaction. Coupling SIT with European Centre Hamburg Model, Version 5 (ECHAM5); Community Atmosphere Model, Version 5 (CAM5); and High Resolution Atmospheric Model (HiRAM) significantly improved MJO simulation in three coupled AGCMs compared with the AGCM driven with prescribed SST. This study suggests two major improvements to the coupling process. First, during the preconditioning phase of MJO over Maritime Continent (MC), the over underestimated surface latent heat bias in AGCMs can be corrected. Second, during the phase of strongest convection over MC, the change of the intraseasonal circulation in the meridional circulation is the dominant factor in the coupled simulations relative to the uncoupled experiments. The study results indicate that a fine vertical resolution near the surface, which better captures temperature variations in the upper few meters of the ocean, considerably improves different models with different configurations and physical parameterization schemes; this could be an essential factor for accurate MJO simulation.

Ozone-Gravity Wave Interaction in the Upper Stratosphere/Lower Mesosphere

The increase in amplitudes of upward propagating gravity waves (GWs) with height due to decreasing density is usually described by exponential growth; however, recent measurements detected a much stronger increase in gravity wave potential energy density (GWPED) during daylight than night-time (increase by a factor of about 4 to 8 between middle stratosphere and upper mesosphere), which is not well understood up to now. This paper suggests that ozone-gravity wave interaction in the upper stratosphere/lower mesosphere is largely responsible for this phenomenon. The coupling between ozone-photochemistry and temperature is particularly strong in the upper stratosphere where the time-mean ozone mixing ratio is decreasing with height; therefore, an initial uplift of an air parcel must lead to a local increase in ozone and in the heating rate compared to the environment, and, hence, to an amplification of the initial uplift. Standard solutions of upward propagating GWs with linear ozone-temperature coupling are formulated suggesting local amplitude amplifications during daylight of 5 to 15 % for low-frequency GWs (periods ≥4 hours), as a function of the intrinsic frequency which decreases if ozone-temperature coupling is included. Subsequently, for horizontal wavelengths larger than 500 km and vertical wavelengths smaller than 5 km, the cumulative amplification during the upward level-by-level propagation leads to much stronger amplitudes in the GW perturbations (factor of about 1.5 to 3) and in the GWPED (factor of about 3 to 9) at upper mesospheric altitudes. The results open a new viewpoint for improving general circulation models with resolved or parameterized GWs.

Soil, Water, and Climate Change Integrated Impact Assessment on Yields

This article describes the potential yields of maize, wheat and barley which were modeled with climate change, soil degradation and water balance scenarios in central Mexico. Two adaptation measures were also evaluated. To estimate yields the AquaCrop-FAO model was applied. Three study cases were chosen and their climate, soil, phenological and management information was compiled. Once calibrated, the authors tested the response in yields for 28 climate change scenarios: five General Circulation Models, two RCP and three-time horizons. Two adaptation actions were evaluated: changing planting date and increase of organic mulches. Results show that yield of maize in the near future (2015-2039) would fall 50% average, barley and wheat yields would decrease in 40% and 25% respectively. If soil degradation and loss is considered, the yield will reduce considerably. Adaptation measure based on changing planting date was as effective as increasing mulches. It is necessary to consider soil together with climate change scenarios in yield modeling. It is possible to suggest wrong adaptation measures if only the climate is considered and not all the variables involved.

Understanding biosphere-precipitation relationships: Theory, model simulations and logical inferences

The four major biophysical controls of vegetation which govern land-atmosphere interaction emanate from the ability or vegetation to. (a) evapotranspire (b) trap solar radiation within leaf organizations. (c) regulate evapotranspiration by stomatal control and (d) modify (generally increase) the surface roughness on the scale of turbulent eddies, Simulation studies with General Circulation Models together with a few observational analyses have provided a rational understanding of vegetation-precipitation interaction. In studies with artificially enhanced vegetation-related processes a strong dependence of rainfall on vegetation has been inferred. For Sahelian and other tropical desert-border regions, where evapotranspiration is small, increasing the surface-albedo (desertification) decreases rainfall. When evaportranspiration and or land-surface roughness are increased in some selected regions - a potential effect of vegetation an increase in local rainfall is produced. The above effects both individually and jointly have simulated increased monsoon rainfall over the Indian subcontinent. Modelling studies directed at understanding the relationship between tropical forests and rainfall with realistic models of the biosphere have simulated a warmer and drier climate in response to Amazonian deforestation. Since forests absorb more solar energy and produce much larger evaportranspiration, as well as moisture convergence through the surface-roughness effect, positive feedback effect of forests on precipitation can be expected naturally. Our new simulation experiments not only reaffirmed the above results but also suggested potential global consequences due to the ongoing deforestation. From a synthesis of modeling results of the last decade, it if further inferred that variations in the biosphere-atmospheric interactions play an important role in redistributing continental precipitation to fulfill the survival and growth requirements of different biomes: forests, pasture, agricultural lands, and deserts.

Climate Change and Crop Production in Africa

Agriculture, particularly crop production, is an economic activity that is highly dependent upon weather and climate in order to produce the food and fiber necessary to sustain human life. The vulnerability of agriculture to climate change and variability is an issue of major importance to the international scientific community. Greenhouse gas (GHG)-induced climate change would very likely result in significant damage in the agricultural sector in sub-Saharan Africa because the region already endures high heat and low precipitation. General circulation models (GCMs) are the primary source of climate change scenarios which make projections about the degree and timing of climate change. Agriculture has always been dependent on the variability of the climate for the growing season and the state of the land at the start of the growing season. The key for adaptation for crop production to climate change is the predictability of the conditions. What is required is an understanding of the effect on the changing climate on land, water, and temperature.

Exploring the Effects of Active Magnetic Drag in a Gener\al Circulation Model of the Ultrahot Jupiter WASP-76b

Ultrahot Jupiters represent an exciting avenue for testing extreme physics and observing atmospheric circulation regimes not found in our solar system. Their high temperatures result in thermally ionized particles embedded in atmospheric winds interacting with the planet’s interior magnetic field by generating current and experiencing bulk Lorentz force drag. Previous treatments of magnetic drag in 3D general circulation models (GCMs) of ultrahot Jupiters have mostly been uniform drag timescales applied evenly throughout the planet, which neglects the strong spatial dependence of these magnetic effects. In this work, we apply our locally calculated active magnetic drag treatment in a GCM of the planet WASP-76b. We find the effects of this treatment to be most pronounced in the planet’s upper atmosphere, where strong differences between the day and night side circulation are present. These circulation effects alter the resulting phase curves by reducing the hot spot offset and increasing the day–night flux contrast. We compare our models to Spitzer phase curves, which imply a magnetic field of at least 3 G for the planet. We additionally contrast our results to uniform drag timescale models. This work highlights the need for more careful treatment of magnetic effects in atmospheric models of hot gas giants.

Parameterization of submesoscale mixed layer restratification under sea ice

Commonly used parameterization of mixed layer instabilities in general circulation models (Fox-Kemper and Ferrari 2008a) was developed for temperate oceans and does not take into account the presence of sea ice in any way. However, the ice-ocean drag provides a strong mechanical coupling between the sea ice and the surface ocean currents and hence may affect mixed layer restratification processes. Here we use idealized simulations of mixed layer instabilities to demonstrate that the sea ice dramatically suppresses the eddy-driven overturning in the mixed layer by dissipating the eddy kinetic energy generated during instabilities. Considering the commonly-used viscous-plastic sea ice rheology, we developed an improvement to the existing mixed layer overturning parameterization, making it explicitly dependent on sea ice concentration. Below the critical sea ice concentration of about 0.68, the internal sea ice stresses are very weak and the conventional parameterization holds. At higher concentrations, the sea ice cover starts acting as a nearly-immobile surface lid, inducing strong dissipation of submesoscale eddies and reducing the intensity of the restratification streamfunction up to a factor of 4 for a fully ice-covered ocean. Our findings suggest that climate projection models might be exaggerating the restratification processes under sea ice, which could contribute to biases in mixed layer depth, salinity, ice-ocean heat fluxes, and sea ice cover.

Parameterized orographic gravity wave drag in CMIP6 models, distribution, variability, trends and intermodel spread

<p>Internal gravity waves (GWs) are a naturally occurring and intermittent phenomenon in the atmosphere. GWs can propagate horizontally and vertically and are important for atmospheric dynamics, influencing the atmospheric thermal and dynamical structure. Research on GWs is connected with some of the most challenging issues of Earth climate and atmospheric science. Consideration of GW-related processes is necessary for a proper description and modelling of the middle and upper atmosphere. However, as GWs exist on scales from a few to thousands of kilometers, they cannot be fully resolved by general circulation models (GCMs) and hence have to be parameterized. Although recently satellite and reanalysis datasets with improved resolution and novel analysis methods together with high-resolution atmospheric models have been tightening the constraints for GW parameterizations in GCMs, the parameterized GW effects still bear a significant margin of uncertainty.</p> <p>To quantify this uncertainty, we analyze the three-dimensional distribution and interannual variability of orographic gravity wave drag (OGWD) in chemistry-climate model simulations. For this, we use a set of AMIP simulations produced within the CMIP6 activity. In particular, we focus on the intermodel spread in the vertical and horizontal OGWD distribution. The different models generaly agree on the areas of the OGWD hotspots. However, in all these regions we find considerable intermodel differences in OGWD magnitude as well as in the altitude of the strongest GW dissipation. In this presentation, we show our findings and discuss possible explanations for the intermodel differences, like different parametrization schemes and choices of tunable parameters.</p>

Statistical interpretation of general circulation model: A prospect for automation of medium range local weather forecast in India

The General Circulation Models (GCM), though able to provide reasonably good medium range weather forecast. have comparatively less skill in forecasting location-specific weather. This is mainly due to the poor representation of 16cal topography and other features in these models. Statistical interpretation (SI) of GCM is very essential in order to improve the location-specific medium range local weather forecast. An attempt has been made at the National Centre for Medium Range Weather Forecasting (NCMRWF), New Delhi to do this type of objective forecasting. Hence location-specific SI models are developed and a bias free forecast is obtained. One of the techniques for accomplishing this, is the Perfect Prog. Method (PPM). PPM models for precipitation (quantitative, probability, yes/no) and maximum minimum temperature are developed for monsoon season (June to August) for 10 stations in lndia. These PPM models and the output from the GCM (R-40) operational at NCMRWF, are then used to obtain the SI forecast. An indirect method based upon SI forecast and observed values of previous one or two seasons, for getting bias free forecast is explained. A comparative study of skill of bias free SI and final forecast, with the observed, issued from NCMRWF to 10 Agromet Field Units (AMFU) during monsoon season 1993, has indicated that automation of medium range local weather forecast can be achieved with the help of SI forecast.