Diagnosing ENSO and global warming tropical precipitation shifts using surface relative humidity and temperature

This is the final version of the article. Available from American Meteorological Society via the DOI in this recordLarge uncertainty remains in future projections of tropical precipitation change under global warming. A simplified method for diagnosing tropical precipitation change is tested here on present day El Niño-Southern Oscillation (ENSO) precipitation shifts. This method, based on the weak temperature gradient approximation, assumes precipitation is associated with local surface relative humidity (RH) and air temperature (SAT), relative to the tropical mean. Observed and simulated changes in RH and SAT are subsequently used to diagnose changes in precipitation. Present day ENSO precipitation shifts are successfully diagnosed using observations (r = 0:69), and an ensemble of atmosphere-only (0:51 ≤ r ≤ 0:8) and coupled (0:5 ≤ r ≤ 0:87) climate model simulations. RH (r = 0:56) is much more influential than SAT (r = 0:27) in determining ENSO precipitation shifts for observations and climate model simulations over both land and ocean. Using inter-model differences, a significant relationship is demonstrated between method performance over ocean for present day ENSO and projected global warming (r = 0:68). As a caveat, we note that mechanisms leading to ENSO-related precipitation changes are not a direct analogue for global warming-related precipitation changes. The diagnosis method presented here demonstrates plausible mechanisms which relate changes in precipitation, RH and SAT under different climate perturbations. Therefore, uncertainty in future tropical precipitation changes may be linked with uncertainty in future RH and SAT changes.AT was supported by a NERC studentship NE/M009599/1 and CASE funding from the Met Office. FHL was part supported by the UK-China Research and Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund. RC was supported by the Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil)

Surface warming and atmospheric circulation dominate rainfall changes over tropical rainforests under global warming

This is the final version. Avaiolable on open access from AGU via the DOI in this recordThis study investigates how the direct effects of CO2 quadrupling on plant physiology impact precipitation in three main rainforests. We show that differences between the regions lie in how land‐surface warming (driven by reduced transpiration) interacts with their climatological atmospheric circulations, regardless of their reliance on evapotranspiration. Various atmosphere‐only experiments from two General Circulation Models are used. We find that over New Guinea, land‐surface warming amplifies moisture convergence from the ocean and increases rainfall. In the Congo, no clear rainfall changes emerge as the land‐surface warming effect is offset by migrations of rainfall. In Amazonia, the interaction of land‐surface warming with the climatological circulation pattern leads to a precipitation‐change dipole, with reduced rainfall in central and eastern Amazonia and increased rainfall in the west.Natural Environmental Research Council (NERC

How certain is ‘certain’?: exploring how the English-language media reported the use of calibrated language in the Intergovernmental Panel on Climate Change’s Fifth Assessment Report

This article presents findings from an analysis of English-language media reports following the publication of the fifth Intergovernmental Panel on Climate Change Assessment Report in September 2013. Focusing on the way they reported the Intergovernmental Panel on Climate Change’s use of ‘calibrated’ language, we find that of 1906 articles relating to the issuing of the report only 272 articles (14.27%) convey the use of a deliberate and systematic verbal scale. The Intergovernmental Panel on Climate Change’s carefully calibrated language was rarely discussed or explicated, but in some instances scientists, political actors or journalists would attempt to contextualise or elaborate on the reported findings by using analogies to other scientific principles or examples of taking action despite uncertainty. We consider those analogies in terms of their efficacy in communicating (un)certainty

Future Changes to El Niño Teleconnections over the North Pacific and North America

This is the final version. Available from the American Meteorological Society via the DOI in this record.Data availability statement. The CMIP6 data used in this study are available for download at https://esgf-node.llnl.gov/ search/cmip6/. ERA5 data are available for download from the Copernicus Climate Change Service Climate Data Store at https:// cds.climate.copernicus.eu/#!/search?text5ERA5&type5dataset.The El Niño-Southern Oscillation (ENSO) is the leading mode of interannual climate variability and it exerts a strong influence on many remote regions of the world, for example in northern North America. Here, we examine future changes to the positive-phase ENSO teleconnection to the North Pacific/North America sector and investigate the mechanisms involved. We find that the positive temperature anomalies over Alaska and northern North America that are associated with an El Niño event in the present day are much weaker, or of the opposite sign, in the CMIP6 abrupt 4×CO2 experiments for almost all models (22 out of 26, of which 15 are statistically significant differences). This is largely related to changes to the anomalous circulation over the North Pacific, rather than differences in the equator-to-pole temperature gradient. Using a barotropic model, run with different background circulation basic states and Rossby wave source forcing patterns from the individual CMIP6 models, we find that changes to the forcing from the equatorial central Pacific precipitation anomalies are more important than changes in the global basic state background circulation. By further decomposing this forcing change into changes associated with the longitude and magnitude of ENSO precipitation anomalies, we demonstrate that the projected overall eastward shift of ENSO precipitation is the main driver of the temperature teleconnection change, rather than the increase in magnitude of El Niño precipitation anomalies which are, nevertheless, seen in the majority of models.Natural Environment Research Council (NERC

An Estimation of the Entomological Inoculation Rate for Ifakara: A Semi-Urban Area in a Region of Intense Malaria Transmission in Tanzania.

An entomological study on vectors of malaria and their relative contribution to Plasmodium falciparum transmission in the semi-urban area of Ifakara, south-eastern Tanzania, was conducted. A total of 32 houses were randomly sampled from the area and light trap catches (LTC) performed in one room in each house every 2 weeks for 1 year. A total of 147 448 mosquitoes were caught from 789 LTC; 26 134 Anopheles gambiae s.l., 615 A. funestus, 718 other anophelines and 119 981 culicines. More than 60% of the total A. gambiae s.l. were found in five (0.6%) LTCs, with a maximum of 5889 caught in a single trap. Of 505 A. gambiae s.l. speciated by polymerase chain reaction, 91.5% were found to be A. arabiensis. Plasmodium falciparum sporozoite enzyme-linked immunosorbent assay tests were performed on 10 108 anopheles mosquitoes and 39 (0.38%) were positive. Entomological inoculation rate (EIR) estimates were generated using a standard method and an alternative method that allows the calculation of confidence intervals based on a negative binomial distribution of sporozoite positive mosquitoes. Overall EIR estimates were similar; 31 vs. 29 [95% confidence interval (CI): 19, 44] infectious bites per annum, respectively. The EIR ranged from 4 (95% CI: 1, 17) in the cool season to 108 (95% CI: 69, 170) in the wet season and from 54 (95% CI: 30, 97) in the east of the town to 15 (95% CI: 8, 30) in the town centre. These estimates show large variations over short distances in time and space. They are all markedly lower than those reported from nearby rural areas and for other parts of Tanzania

The impact of a uniform ocean warming on the West African monsoon

This is the final version. Available on open access from Springer via the DOI in this recordAvailability of data and materials: CMIP6 data was accessed from the ESGF CEDA data node https://esgf-index1.ceda.ac.uk/search/cmip6-ceda/. Data from the HadGEM2-A spin-up experiments are archived at the Met Office and available from the authors on request for research purposes.Projections of West African Monsoon (WAM) precipitation are uncertain. To address this, an improved understanding of the mechanisms driving WAM precipitation change is needed to shed light on inter-model differences and aid model development. The full forcing of increased CO2 can be decomposed into different components such as the impact of ocean warming, or the direct radiative effect of increased CO2. This paper investigates such a decomposition, analysing the effect of a uniform 4K ocean warming whilst keeping atmospheric CO2 concentrations constant. The analysis highlights several mechanisms acting to decrease WAM precipitation over a range of timescales, from days after the abrupt ocean warming, to the long-term equilibrium response. The initial decrease in WAM precipitation is caused by warming and enhanced convection over the ocean, stabilising the atmosphere inland and disrupting the monsoon inflow at low levels. Later in the response (after about 5 days), the WAM precipitation is reduced through a strengthening of the shallow circulation over West Africa, associated with changes in the large-scale temperature gradients and a local warming of the atmosphere related to a soil moisture feedback mechanism over the Sahel. Finally, from around 20 days after the SST increase, the WAM precipitation is also reduced through changes in specific humidity gradients that lead to increased potency of dry air advection into the monsoon rainband. The analysis concludes by demonstrating that the processes affecting precipitation in the early stages of the response are also relevant to the long-term equilibrium response.Natural Environment Research Council (NERC)UK-China Research & Innovation Partnership Fund

Targeting the X Chromosome during Spermatogenesis Induces Y Chromosome Transmission Ratio Distortion and Early Dominant Embryo Lethality in Anopheles gambiae

We have exploited the high selectivity of the homing endonuclease I-PpoI for the X-linked Anopheles gambiae 28S ribosomal genes to selectively target X chromosome carrying spermatozoa. Our data demonstrated that in heterozygous males, the expression of I-PpoI in the testes induced a strong bias toward Y chromosome–carrying spermatozoa. Notably, these male mosquitoes also induced complete early dominant embryo lethality in crosses with wild-type females. Morphological and molecular data indicated that all spermatozoa, irrespectively of the inheritance of the transgene, carried a substantial amount of I-PpoI protein that could attack the maternally inherited chromosome X of the embryo. Besides the obvious implications for implementing vector control measures, our data demonstrated the feasibility of generating synthetic sex distorters and revealed the intriguing possibility of manipulating maternally inherited genes using wild-type sperm cells carrying engineered endonucleases

Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study

Background: There is no consensus on the most appropriate approach to handle missing covariate data within prognostic modelling studies. Therefore a simulation study was performed to assess the effects of different missing data techniques on the performance of a prognostic model. Methods: Datasets were generated to resemble the skewed distributions seen in a motivating breast cancer example. Multivariate missing data were imposed on four covariates using four different mechanisms; missing completely at random (MCAR), missing at random (MAR), missing not at random (MNAR) and a combination of all three mechanisms. Five amounts of incomplete cases from 5% to 75% were considered. Complete case analysis (CC), single imputation (SI) and five multiple imputation (MI) techniques available within the R statistical software were investigated: a) data augmentation (DA) approach assuming a multivariate normal distribution, b) DA assuming a general location model, c) regression switching imputation, d) regression switching with predictive mean matching (MICE-PMM) and e) flexible additive imputation models. A Cox proportional hazards model was fitted and appropriate estimates for the regression coefficients and model performance measures were obtained. Results: Performing a CC analysis produced unbiased regression estimates, but inflated standard errors, which affected the significance of the covariates in the model with 25% or more missingness. Using SI, underestimated the variability; resulting in poor coverage even with 10% missingness. Of the MI approaches, applying MICE-PMM produced, in general, the least biased estimates and better coverage for the incomplete covariates and better model performance for all mechanisms. However, this MI approach still produced biased regression coefficient estimates for the incomplete skewed continuous covariates when 50% or more cases had missing data imposed with a MCAR, MAR or combined mechanism. When the missingness depended on the incomplete covariates, i.e. MNAR, estimates were biased with more than 10% incomplete cases for all MI approaches. Conclusion: The results from this simulation study suggest that performing MICE-PMM may be the preferred MI approach provided that less than 50% of the cases have missing data and the missing data are not MNAR