“…We used the R package RNCEP (Kemp et al., 2012) to gather National Center for Environmental Prediction (NCEP) Reanalysis I data (Kalnay et al., 1996; Kanamitsu et al., 2002) on temperature, precipitation, and wind in an area from about 119° to 83°W and 11° to 38°N (see maps in Appendix S1), which includes the entire countries of Honduras, El Salvador, Guatemala, Belize, and Mexico, and 20 south‐western states of the United States partly or entirely. Ocean grid cells were masked from the analysis.…”
Climate change is drastically changing the timing of biological events across the globe. Changes in the phenology of seasonal migrations between the breeding and wintering grounds have been observed across biological taxa, including birds, mammals, and insects. For birds, strong links have been shown between changes in migration phenology and changes in weather conditions at the wintering, stopover, and breeding areas. For other animal taxa, the current understanding of, and evidence for, climate (change) influences on migration still remains rather limited, mainly due to the lack of long‐term phenology datasets. Bracken Cave in Texas (USA) holds one of the largest bat colonies of the world. Using weather radar data, a unique 23‐year (1995–2017) long time series was recently produced of the spring and autumn migration phenology of Brazilian free‐tailed bats (Tadarida brasiliensis) at Bracken Cave. Here, we analyse these migration phenology time series in combination with gridded temperature, precipitation, and wind data across Mexico and southern USA, to identify the climatic drivers of (changes in) bat migration phenology. Perhaps surprisingly, our extensive spatiotemporal search did not find temperature to influence either spring or autumn migration. Instead, spring migration phenology seems to be predominantly driven by wind conditions at likely wintering or spring stopover areas during the migration period. Autumn migration phenology, on the other hand, seems to be dominated by precipitation to the east and north‐east of Bracken Cave. Long‐term changes towards more frequent migration and favourable wind conditions have, furthermore, allowed spring migration to occur 16 days earlier. Our results illustrate how some of the remaining knowledge gaps on the influence of climate (change) on bat migration and abundance can be addressed using weather radar analyses.
“…We used the R package RNCEP (Kemp et al., 2012) to gather National Center for Environmental Prediction (NCEP) Reanalysis I data (Kalnay et al., 1996; Kanamitsu et al., 2002) on temperature, precipitation, and wind in an area from about 119° to 83°W and 11° to 38°N (see maps in Appendix S1), which includes the entire countries of Honduras, El Salvador, Guatemala, Belize, and Mexico, and 20 south‐western states of the United States partly or entirely. Ocean grid cells were masked from the analysis.…”
Climate change is drastically changing the timing of biological events across the globe. Changes in the phenology of seasonal migrations between the breeding and wintering grounds have been observed across biological taxa, including birds, mammals, and insects. For birds, strong links have been shown between changes in migration phenology and changes in weather conditions at the wintering, stopover, and breeding areas. For other animal taxa, the current understanding of, and evidence for, climate (change) influences on migration still remains rather limited, mainly due to the lack of long‐term phenology datasets. Bracken Cave in Texas (USA) holds one of the largest bat colonies of the world. Using weather radar data, a unique 23‐year (1995–2017) long time series was recently produced of the spring and autumn migration phenology of Brazilian free‐tailed bats (Tadarida brasiliensis) at Bracken Cave. Here, we analyse these migration phenology time series in combination with gridded temperature, precipitation, and wind data across Mexico and southern USA, to identify the climatic drivers of (changes in) bat migration phenology. Perhaps surprisingly, our extensive spatiotemporal search did not find temperature to influence either spring or autumn migration. Instead, spring migration phenology seems to be predominantly driven by wind conditions at likely wintering or spring stopover areas during the migration period. Autumn migration phenology, on the other hand, seems to be dominated by precipitation to the east and north‐east of Bracken Cave. Long‐term changes towards more frequent migration and favourable wind conditions have, furthermore, allowed spring migration to occur 16 days earlier. Our results illustrate how some of the remaining knowledge gaps on the influence of climate (change) on bat migration and abundance can be addressed using weather radar analyses.
“…The annual mean precipitation is about 1400 mm, peaking (900 mm) during the summer (June through September), and significantly decreasing (80 mm) in the winter (December to February). Figure 1.Study locations and the general circulation pattern of the Asian summer monsoon (ASM; June–August) between 1979 and 2016 (NCAR/NCFP, Kalnay et al, 1996). The red star represents Wulu (WL) Cave, and the white stars show Tian'e (TE; Zhang et al, 2018) and Yongxing Caves (YX; Chen et al, 2016).…”
Section: Cave Site Sample and Methodsmentioning
confidence: 99%
“…Study locations and the general circulation pattern of the Asian summer monsoon (ASM; June–August) between 1979 and 2016 (NCAR/NCFP, Kalnay et al, 1996). The red star represents Wulu (WL) Cave, and the white stars show Tian'e (TE; Zhang et al, 2018) and Yongxing Caves (YX; Chen et al, 2016).…”
A 20-year-resolution speleothem δ18O record from southern China reveals a detailed Asian summer monsoon (ASM) history between 73.6 and 62.3 ka. ASM changes during Interstadial 19 and late MIS 4 matched Greenland temperature variations but were antiphased with Antarctic temperatures. However, long-term strengthening of the ASM in early MIS 4 agrees well with the gradual Antarctic warming, when Greenland remained in a stable cold state. More specifically, the ASM was less variable during peak interstadials in contrast to striking instabilities during stadials. These observations suggest that the factors dominating ASM variability change through time. During early MIS 4, negligible freshwater perturbations occurred in the North Atlantic, and sea-surface temperatures in the low- to midlatitude Pacific Ocean reached the modern level. Thus, an expansion of the Intertropical Convergence Zone (ITCZ) was likely important for the long-term ASM rise. In late MIS 4, the antiphase correlation between ASM and Antarctic temperature could be attributed to freshwater inputs into the North Atlantic and a southerly positioned ITCZ. Consequently, meridional ITCZ shifts, although within a limited latitudinal band, would result in an antiphase relationship between interhemispheric climate changes. Otherwise, an in-phase correlation could be expected if the centroid of ITCZ is stable along the equator.
“…A horizontal curvilinear grid is adopted with an average spatial resolution of 10 km, and the terrain‐following s‐ordinate with 40 levels in the vertical axis is applied. The daily atmospheric forcing fields from the U.S. National Centers of Environmental Prediction reanalysis project (Kalnay et al, 1996), including heat fluxes, solar radiation fluxes, evaporation‐precipitation (E‐P), air temperature, and specific humidity, are used to force the model. The daily mean wind field from the Cross‐Calibrated Multi‐Platform (CCMP) ocean surface wind product with a spatial resolution of (1/4)° is employed (from http://www.remss.com/measurements/ccmp/), which is converted into wind stress using the bulk formula given by Large and Pond (1982).…”
This study investigates the impact of assimilation of Northwestern Tropical Pacific Ocean (NWTPO) moored currents observation system on low‐frequency (over a period of more than 90 days) current estimation. A low‐frequency scale‐selective ensemble optimal interpolation (EnOI) scheme is designed to assimilate the horizontally sparse moored currents into an eddy‐permitting ocean model. In this assimilation scheme, low‐frequency current signals are selected by removing intraseasonal signals in both observation and ensemble data, and a horizontal spatial filter is implemented to match the model forecast to the low‐frequency ensemble and observation. The assimilation of currents efficiently resolves simulated low‐frequency current displacements, especially for the Equatorial Undercurrent (EUC), the North Equatorial Countercurrent (NECC), and the North Equatorial Current (NEC). More realistic intensities of the NWTPO low‐frequency currents are also reproduced. With respect to the moored velocity profiles, the root‐mean‐square error (RMSE) of the simulated low‐frequency zonal velocity above a 500‐m depth is reduced from 10.9 to 5.8 cm/s using this low‐frequency EnOI scheme. The low‐frequency variation of NWTPO currents is reproduced by correcting the structures of different baroclinic modes. The increments of zonal velocities mainly correspond to the first baroclinic mode for the NECC and NEC, while for the EUC, they correspond to the leading three and higher‐order baroclinic modes. The improvements of the simulated stratification and pressure gradient remark the role of the assimilation of moored currents in adjusting available potential energy.
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