How Skillful are the Multiannual Forecasts of Atlantic Hurricane Activity?

The recent emergence of near-term climate prediction, wherein climate models are initialized with the contemporaneous state of the Earth system and integrated up to 10 years into the future, has prompted the development of three different multiannual forecasting techniques of North Atlantic hurricane frequency. Descriptions of these three different approaches, as well as their respective skill, are available in the peer-reviewed literature, but because these various studies are sufficiently different in their details (e.g., period covered, metric used to compute the skill, measure of hurricane activity), it is nearly impossible to compare them. Using the latest decadal reforecasts currently available, we present a direct comparison of these three multiannual forecasting techniques with a combination of simple statistical models, with the hope of offering a perspective on the current state-of-the-art research in this field and the skill level currently reached by these forecasts. Using both deterministic and probabilistic approaches, we show that these forecast systems have a significant level of skill and can improve on simple alternatives, such as climatological and persistence forecasts.The first author would like to thank Isadora Jimenez for providing the necessary material for Fig. 2. The first author would like to acknowledge the financial support from the Ministerio de Economía, Industria y Competitividad (MINECO; Project CGL2014- 55764-R), the Risk Prediction Initiative at BIOS (Grant RPI2.0-2013-CARON), and the EU [Seventh Framework Programme (FP7); Grant Agreement GA603521]. We additionally acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP, the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. LPC's contract is cofinanced by the MINECO under the Juan de la Cierva Incorporacion postdoctoral fellowship number IJCI-2015-23367. Finally, we thank the National Hurricane Center for making the HURDAT2 data available. All climate model data are available at https://esgf-index1.ceda.ac.uk/projects/esgf-ceda/.Peer ReviewedPostprint (published version

Thermodynamic and Dynamic Mechanisms for Large-Scale Changes in the Hydrological Cycle in Response to Global Warming

The mechanisms of changes in the large-scale hydrological cycle projected by 15 models participating in the Coupled Model Intercomparison Project phase 3 and used for the Intergovernmental Panel on Climate Change’s Fourth Assessment Report are analyzed by computing differences between 2046 and 2065 and 1961 and 2000. The contributions to changes in precipitation minus evaporation, P − E, caused thermodynamically by changes in specific humidity, dynamically by changes in circulation, and by changes in moisture transports by transient eddies are evaluated. The thermodynamic and dynamic contributions are further separated into advective and divergent components. The nonthermodynamic contributions are then related to changes in the mean and transient circulation. The projected change in P − E involves an intensification of the existing pattern of P − E with wet areas [the intertropical convergence zone (ITCZ) and mid- to high latitudes] getting wetter and arid and semiarid regions of the subtropics getting drier. In addition, the subtropical dry zones expand poleward. The accentuation of the twentieth-century pattern of P − E is in part explained by increases in specific humidity via both advection and divergence terms. Weakening of the tropical divergent circulation partially opposes the thermodynamic contribution by creating a tendency to decreased P − E in the ITCZ and to increased P − E in the descending branches of the Walker and Hadley cells. The changing mean circulation also causes decreased P − E on the poleward flanks of the subtropics because the descending branch of the Hadley Cell expands and the midlatitude meridional circulation cell shifts poleward. Subtropical drying and poleward moistening are also contributed to by an increase in poleward moisture transport by transient eddies. The thermodynamic contribution to changing P − E, arising from increased specific humidity, is almost entirely accounted for by atmospheric warming under fixed relative humidity

Thermodynamic and Dynamic Mechanisms for Large-Scale Changes in the Hydrological Cycle in Response to Global Warming

The mechanisms of changes in the large-scale hydrological cycle projected by 15 models participating in the Coupled Model Intercomparison Project phase 3 and used for the Intergovernmental Panel on Climate Change’s Fourth Assessment Report are analyzed by computing differences between 2046 and 2065 and 1961 and 2000. The contributions to changes in precipitation minus evaporation, P − E, caused thermodynamically by changes in specific humidity, dynamically by changes in circulation, and by changes in moisture transports by transient eddies are evaluated. The thermodynamic and dynamic contributions are further separated into advective and divergent components. The nonthermodynamic contributions are then related to changes in the mean and transient circulation. The projected change in P − E involves an intensification of the existing pattern of P − E with wet areas [the intertropical convergence zone (ITCZ) and mid- to high latitudes] getting wetter and arid and semiarid regions of the subtropics getting drier. In addition, the subtropical dry zones expand poleward. The accentuation of the twentieth-century pattern of P − E is in part explained by increases in specific humidity via both advection and divergence terms. Weakening of the tropical divergent circulation partially opposes the thermodynamic contribution by creating a tendency to decreased P − E in the ITCZ and to increased P − E in the descending branches of the Walker and Hadley cells. The changing mean circulation also causes decreased P − E on the poleward flanks of the subtropics because the descending branch of the Hadley Cell expands and the midlatitude meridional circulation cell shifts poleward. Subtropical drying and poleward moistening are also contributed to by an increase in poleward moisture transport by transient eddies. The thermodynamic contribution to changing P − E, arising from increased specific humidity, is almost entirely accounted for by atmospheric warming under fixed relative humidity

A dynamical statistical framework for seasonal streamflow forecasting in an agricultural watershed

The state of Iowa in the US Midwest is regularly affected by major floods and has seen a notable increase in agricultural land cover over the twentieth century. We present a novel statistical-dynamical approach for probabilistic seasonal streamflow forecasting using land cover and General Circulation Model (GCM) precipitation forecasts. Low to high flows are modelled and forecast for the Raccoon River at Van Meter, a 8900 km2 catchment located in central-western Iowa. Statistical model fits for each streamflow quantile (from seasonal minimum to maximum; predictands) are based on observed basin-averaged total seasonal precipitation, annual row crop (corn and soybean) production acreage, and observed precipitation from the month preceding each season (to characterize antecedent wetness conditions) (predictors). Model fits improve when including agricultural land cover and antecedent precipitation as predictors, as opposed to just precipitation. Using the dynamically-updated relationship between predictand and predictors every year, forecasts are computed from 1 to 10 months ahead of every season based on annual row crop acreage from the previous year (persistence forecast) and the monthly precipitation forecasts from eight GCMs of the North American Multi-Model Ensemble (NMME). The skill of our forecast streamflow is assessed in deterministic and probabilistic terms for all initialization months, flow quantiles, and seasons. Overall, the system produces relatively skillful streamflow forecasts from low to high flows, but the skill does not decrease uniformly with initialization time, suggesting that improvements can be gained by using different predictors for specific seasons and flow quantiles

Testing the Performance of Tropical Cyclone Genesis Indices in Future Climates Using the HiRAM Model

Tropical cyclone genesis indices (TCGIs) are functions of the large-scale environment that are designed to be proxies for the probability of tropical cyclone (TC) genesis. While the performance of TCGIs in the current climate can be assessed by direct comparison to TC observations, their ability to represent future TC activity based on projections of the large-scale environment cannot. Here the authors examine the performance of TCGIs in high-resolution atmospheric model simulations forced with sea surface temperatures (SST) of future, warmer climate scenarios. They investigate whether the TCGIs derived for the present climate can, when computed from large-scale fields taken from future climate simulations, capture the simulated global mean decreases in TC frequency. The TCGIs differ in their choice of environmental predictors, and several choices of predictors perform well in the present climate. However, some TCGIs that perform well in the present climate do not accurately reproduce the simulated future decrease in TC frequency. This decrease is captured when the humidity predictor is the column saturation deficit rather than relative humidity. Using saturation deficit with relative SST as the other thermodynamic predictor overpredicts the TC frequency decrease, while using potential intensity in place of relative SST as the other thermodynamic predictor gives a good prediction of the decrease’s magnitude. These positive results appear to depend on the spatial and seasonal patterns in the imposed SST changes; none of the indices capture correctly the frequency decrease in simulations with spatially uniform climate forcings, whether a globally uniform increase in SST of 2 K, or a doubling of CO2 with no change in SST

Excess body weight in children may increase the length of hospital stay

OBJECTIVES: To investigate the prevalence of excess body weight in the pediatric ward of University Hospital and to test both the association between initial nutritional diagnosis and the length of stay and the in-hospital variation in nutritional status. METHODS: Retrospective cohort study based on information entered in clinical records from University Hospital. The data were collected from a convenience sample of 91 cases among children aged one to 10 years admitted to the hospital in 2009. The data that characterize the sample are presented in a descriptive manner. Additionally, we performed a multivariate linear regression analysis adjusted for age and gender. RESULTS: Nutritional classification at baseline showed that 87.8% of the children had a normal weight and that 8.9% had excess weight. The linear regression models showed that the average weight loss z-score of the children with excess weight compared with the group with normal weight was −0.48 (p = 0.018) and that their length of stay was 2.37 days longer on average compared with that of the normal-weight group (p = 0.047). CONCLUSIONS: The length of stay and loss of weight at the hospital may be greater among children with excess weight than among children with normal weight

Multi-Annual Climate Predictions for Fisheries: An Assessment of Skill of Sea Surface Temperature Forecasts for Large Marine Ecosystems

Decisions made by fishers and fisheries managers are informed by climate and fisheries observations that now often span more than 50 years. Multi-annual climate forecasts could further inform such decisions if they were skillful in predicting future conditions relative to the 50-year scope of past variability. We demonstrate that an existing multi-annual prediction system skillfully forecasts the probability of next year, the next 1–3 years, and the next 1–10 years being warmer or cooler than the 50-year average at the surface in coastal ecosystems. Probabilistic forecasts of upper and lower seas surface temperature (SST) terciles over the next 3 or 10 years from the GFDL CM 2.1 10-member ensemble global prediction system showed significant improvements in skill over the use of a 50-year climatology for most Large Marine Ecosystems (LMEs) in the North Atlantic, the western Pacific, and Indian oceans. Through a comparison of the forecast skill of initialized and uninitialized hindcasts, we demonstrate that this skill is largely due to the predictable signature of radiative forcing changes over the 50-year timescale rather than prediction of evolving modes of climate variability. North Atlantic LMEs stood out as the only coastal regions where initialization significantly contributed to SST prediction skill at the 1 to 10 year scale

Epidemic dynamics of respiratory syncytial virus in current and future climates.

A key question for infectious disease dynamics is the impact of the climate on future burden. Here, we evaluate the climate drivers of respiratory syncytial virus (RSV), an important determinant of disease in young children. We combine a dataset of county-level observations from the US with state-level observations from Mexico, spanning much of the global range of climatological conditions. Using a combination of nonlinear epidemic models with statistical techniques, we find consistent patterns of climate drivers at a continental scale explaining latitudinal differences in the dynamics and timing of local epidemics. Strikingly, estimated effects of precipitation and humidity on transmission mirror prior results for influenza. We couple our model with projections for future climate, to show that temperature-driven increases to humidity may lead to a northward shift in the dynamic patterns observed and that the likelihood of severe outbreaks of RSV hinges on projections for extreme rainfall

Improved ENSO forecasting using Bayesian updating and the North American Multi Model Ensemble (NMME)

This study assesses the forecast skill of eight North American Multi Model Ensemble (NMME) models in predicting Niño3/3.4 indices and improves their skill using Bayesian updating (BU). The forecast skill that is obtained using the ensemble mean of NMME (NMME-EM) shows strong dependence on lead (initial) month and target month, and is quite promising in terms of correlation, root mean square error (RMSE), the standard deviation ratio (SDRatio) and probabilistic Brier Skill Score, especially at short lead months. However, the skill decreases in target months from late spring to summer due to the “Spring Predictability Barrier.” When BU is applied to eight NMME models (BU-Model), the forecasts tend to outperform NMME-EM in predicting Niño3/3.4 in terms of correlation, RMSE, and SDRatio. For Niño3.4, the BU-Model outperforms NMME- EM forecasts for almost all leads (1-12; particularly for short leads) and target months (from January to December). However, for Niño3, the BU-Model does not outperform NMME-EM forecasts for leads 7-11 and target months from June to October in terms of correlation and RMSE. Last, we test further potential improvements by preselecting “good” models (BU-Model-0.3) and by using principal components analysis to remove the multicollinearity among models, but these additional methodologies do not outperform the BU-Model, which produces the best forecasts of Niño3/3.4 for the 2015/2016 El Niño event

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