Seasonal Prediction Potential for Springtime Dustiness in the United States

Most dust forecast models focus on short, subseasonal lead times, that is, 3 to 6 days, and the skill of seasonal prediction is not clear. In this study we examine the potential of seasonal dust prediction in the United States using an observation‐constrained regression model and key variables predicted by a seasonal prediction model developed at National Oceanic and Atmospheric Administration Geophysical Fluid Dynamics Laboratory, the Forecast‐Oriented Low Ocean Resolution (FLOR) model. Our method shows skillful predictions of spring dustiness 3 to 6 months in advance. It is found that the regression model explains about 71% of the variances of dust event frequency over the Great Plains and 63% over the southwestern United States in March‐May from 2004 to 2016 using predictors from FLOR initialized on 1 December. Variations in springtime dustiness are dominated by springtime climatic factors rather than wintertime factors. Findings here will help development of a seasonal dust prediction system and hazard prevention.NASA (NNH14ZDA001N-ACMAP, NNH16ZDA001N-MAP)Princeton University's Cooperative Institute for Climate ScienceNOA

The influence of CO_2 forcing on North American monsoon moisture surges

Widespread multiday convective bursts in the southwestern United States during the North American monsoon are often triggered by Gulf of California moisture surges (GoC surges). However, how GoC surges, and the amount and intensity of associated precipitation, will change in response to CO_2-induced warming remains little known, not least because the most widely available climate models do not currently resolve the relevant mesoscale dynamics due to their coarse resolution (100 km or more). In this study, a 50-km resolution global coupled model (FLOR) is used to address this question. It is found that the mean number of GoC surge events remains unchanged under CO_2 doubling, but intermediate-to-high intensity surge-related precipitation tends to become less frequent, thus reducing the mean summertime rainfall. Lowlevel moisture fluxes associated with GoC surges as well as their convergence over land to the east of the GoC intensify, but the increases in low-level moisture are not matched by the larger increments in the near-surface saturation specific humidity due to amplified land warming. This results in a more unsaturated, low-level atmospheric environment which disfavors moist convection. These thermodynamic changes are accompanied by dynamics changes that are also less conducive to convective activity, with the mid-level monsoonal ridge projected to expand and move to the west of its present-day climatological maximum. Despite the overall reduction in precipitation, the frequency of very intense, localized daily surge-related precipitation in Arizona and surrounding areas is projected to increase, consistently with increased precipitable water

Weakening of the North American monsoon with global warming

Future changes in the North American monsoon, a circulation system that brings abundant summer rains to vast areas of the North American Southwest, could have significant consequences for regional water resources. How this monsoon will change with increasing greenhouse gases, however, remains unclear, not least because coarse horizontal resolution and systematic sea-surface temperature biases limit the reliability of its numerical model simulations. Here we investigate the monsoon response to increased atmospheric carbon dioxide (CO_2) concentrations using a 50-km-resolution global climate model which features a realistic representation of the monsoon climatology and its synoptic-scale variability. It is found that the monsoon response to CO_2 doubling is sensitive to sea-surface temperature biases. When minimizing these biases, the model projects a robust reduction in monsoonal precipitation over the southwestern United States, contrasting with previous multi-model assessments. Most of this precipitation decline can be attributed to increased atmospheric stability, and hence weakened convection, caused by uniform sea-surface warming. These results suggest improved adaptation measures, particularly water resource planning, will be required to cope with projected reductions in monsoon rainfall in the American Southwest

Evaluation of snow cover fraction for regional climate simulations in the Sierra Nevada

Mountain snow cover plays an important role in regional climate due to its high albedo, its effects on atmospheric convection, and its influence on lower-elevation runoff. Snowpack water storage is also a critical water resource and understanding how it varies is of great social value. Unfortunately, in situ measurements of snow cover are not widespread; therefore, models are often depended on to assess snowpack and snow cover variability. Here, we use a new satellite-derived snow product to evaluate the ability of the Weather Research and Forecasting (WRF) regional climate model with the Noah land surface model with multiparameterization options (Noah-MP) to simulate snow cover fraction (SCF) and snow water equivalent (SWE) on a 3 km domain over the central Sierra Nevada. WRF/Noah-MP SWE simulations improve upon previous versions of the Noah land surface model by removing the early bias in snow melt. As a result, WRF/Noah-MP now accurately simulates spatial variations in SWE. Additionally, WRF/Noah-MP correctly identifies the areas where snow is present and captures large-scale variability in SCF. Temporal RMSE of the domain-average SCF was 1863.9 km2 (24%). However, our study reveals that WRF/Noah-MP struggles to simulate SCF at the scale of individual grid cells. The equation used to calculate SCF fails to produce temporal variations in grid-scale SCF and depletion occurs too rapidly. Therefore SCF is a nearly binary metric inmountain environments. Sensitivity tests of the equation may improve simulation of SCF during accumulation or melt but does not remove the bias for the entire snow season. Though WRF/Noah-MP accurately simulates the presence or absence of snow, high-resolution, reliable SCF measurements may only be attainable if snow depletion equations are designed specifically for complex topographical areas

Weakening of the North American monsoon with global warming

Future changes in the North American monsoon, a circulation system that brings abundant summer rains to vast areas of the North American Southwest, could have significant consequences for regional water resources. How this monsoon will change with increasing greenhouse gases, however, remains unclear, not least because coarse horizontal resolution and systematic sea-surface temperature biases limit the reliability of its numerical model simulations. Here we investigate the monsoon response to increased atmospheric carbon dioxide (CO_2) concentrations using a 50-km-resolution global climate model which features a realistic representation of the monsoon climatology and its synoptic-scale variability. It is found that the monsoon response to CO_2 doubling is sensitive to sea-surface temperature biases. When minimizing these biases, the model projects a robust reduction in monsoonal precipitation over the southwestern United States, contrasting with previous multi-model assessments. Most of this precipitation decline can be attributed to increased atmospheric stability, and hence weakened convection, caused by uniform sea-surface warming. These results suggest improved adaptation measures, particularly water resource planning, will be required to cope with projected reductions in monsoon rainfall in the American Southwest

The Impact of Horizontal Resolution on North American Monsoon Gulf of California Moisture Surges in a Suite of Coupled Global Climate Models

The impact of atmosphere and ocean horizontal resolution on the climatology of North American monsoon Gulf of California (GoC) moisture surges is examined in a suite of global circulation models (CM2.1, FLOR, CM2.5, CM2.6, and HiFLOR) developed at the Geophysical Fluid Dynamics Laboratory (GFDL). These models feature essentially the same physical parameterizations but differ in horizontal resolution in either the atmosphere (≃200, 50, and 25 km) or the ocean (≃1°, 0.25°, and 0.1°). Increasing horizontal atmospheric resolution from 200 to 50 km results in a drastic improvement in the model’s capability of accurately simulating surge events. The climatological near-surface flow and moisture and precipitation anomalies associated with GoC surges are overall satisfactorily simulated in all higher-resolution models. The number of surge events agrees well with reanalyses, but models tend to underestimate July–August surge-related precipitation and overestimate September surge-related rainfall in the southwestern United States. Large-scale controls supporting the development of GoC surges, such as tropical easterly waves (TEWs), tropical cyclones (TCs), and trans-Pacific Rossby wave trains (RWTs), are also well captured, although models tend to underestimate the TEW and TC magnitude and number. Near-surface GoC surge features and their large-scale forcings (TEWs, TCs, and RWTs) do not appear to be substantially affected by a finer representation of the GoC at higher ocean resolution. However, the substantial reduction of the eastern Pacific warm sea surface temperature bias through flux adjustment in the Forecast-Oriented Low Ocean Resolution (FLOR) model leads to an overall improvement of tropical–extratropical controls on GoC moisture surges and the seasonal cycle of precipitation in the southwestern United States

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

The Alaskan Summer 2019 Extreme Heat Event: The Role of Anthropogenic Forcing, and Projections of the Increasing Risk of Occurrence

Extreme heat occurred over Alaska in June–July 2019, posing risks to infrastructure, ecosystem, and human health. It is vital to improve our understanding of the causes of such events and the extent to which anthropogenic forcing may alter their likelihood and magnitude. Here, we use multiple large ensembles of climate models, comprising thousands of simulated years, to investigate these issues. Our results suggest that the presence of anthropogenic radiative forcing increased the likelihood of the 2019 extreme heat event by as much as 6%. Further we show the rate of occurrence of such an extreme heat event is likely to substantially increase in the future with increasing levels of atmospheric greenhouse gases. While uncertainty in projected climate risk from model choice leads to a broad range of future extreme heat event probabilities, some models project that with rapidly increasing levels of greenhouse gases the likelihood of such events would exceed 75% by 2090

On the Angola low interannual variability and its role in modulating ENSO effects in Southern Africa.

21 pagesInternational audienceThe Angola low is a summertime low pressure system that affects the convergence of low-level moisture fluxes into southern Africa. Interannual variations of the Angola low reduce the seasonal prediction skills for this region that arise from coupled atmosphere–ocean variability. Despite its importance, the interannual dynamics of the Angola low, and its relationship with El Niño–Southern Oscillation (ENSO) and other coupled modes of variability, are still poorly understood, mostly because of the scarcity of atmospheric data and short-term duration of atmospheric reanalyses in the region. To bypass this issue, we use a long-term (3500 year) run from a 50-km-resolution global coupled model capable of simulating the summertime southern African large-scale circulation and teleconnections. We find that the meridional displacement and strength of the Angola low are moderately modulated by local sea surface temperature anomalies, especially those in proximity of the southeastern African coast, and to a lesser extent by ENSO and the subtropical Indian Ocean dipole. Comparison of the coupled run with a 1000-yr run driven by climatological sea surface temperatures reveals that the interannual excursions of the Angola low are in both cases associated with geopotential height anomalies over the southern Atlantic and Indian Ocean related to extratropical atmospheric variability. Midlatitude atmospheric variability explains almost 60% of the variance of the Angola low variability in the uncoupled run, but only 20% in the coupled run. Therefore, while the Angola low appears to be intrinsically controlled by atmospheric extratropical variability, the interference of the atmospheric response forced by sea surface temperature anomalies weakens this influence

Shifting patterns of mild weather in response to projected radiative forcing

Climate change has been shown to impact the mean climate state and climate extremes. Though climate extremes have the potential to disrupt society, extreme conditions are rare by definition. In contrast, mild weather occurs frequently and many human activities are built around it. We provide a global analysis of mild weather based on simple criteria and explore changes in response to radiative forcing. We find a slight global mean decrease in the annual number of mild days projected both in the near future (−4 days per year, 2016–2035) and at the end of this century (−10 days per year, 2081–2100). Projected seasonal and regional redistributions of mild days are substantially greater. These changes are larger than the interannual variability of mild weather caused by El Niño–Southern Oscillation. Finally, we show an observed global decrease in the recent past, and that observed regional changes in mild weather resemble projections