Lake surface water temperatures of European Alpine lakes (1989–2013) based on the Advanced Very High Resolution Radiometer (AVHRR) 1 km data set

Lake water temperature (LWT) is an important driver of lake ecosystems and it has been identified as an indicator of climate change. Consequently, the Global Climate Observing System (GCOS) lists LWT as an essential climate variable. Although for some European lakes long in situ time series of LWT do exist, many lakes are not observed or only on a non-regular basis making these observations insufficient for climate monitoring. Satellite data can provide the information needed. However, only few satellite sensors offer the possibility to analyse time series which cover 25 years or more. The Advanced Very High Resolution Radiometer (AVHRR) is among these and has been flown as a heritage instrument for almost 35 years. It will be carried on for at least ten more years, offering a unique opportunity for satellite-based climate studies. Herein we present a satellite-based lake surface water temperature (LSWT) data set for European water bodies in or near the Alps based on the extensive AVHRR 1 km data record (1989–2013) of the Remote Sensing Research Group at the University of Bern. It has been compiled out of AVHRR/2 (NOAA-07, -09, -11, -14) and AVHRR/3 (NOAA-16, -17, -18, -19 and MetOp-A) data. The high accuracy needed for climate related studies requires careful pre-processing and consideration of the atmospheric state. The LSWT retrieval is based on a simulation-based scheme making use of the Radiative Transfer for TOVS (RTTOV) Version 10 together with ERA-interim reanalysis data from the European Centre for Medium-range Weather Forecasts. The resulting LSWTs were extensively compared with in situ measurements from lakes with various sizes between 14 and 580 km2 and the resulting biases and RMSEs were found to be within the range of −0.5 to 0.6 K and 1.0 to 1.6 K, respectively. The upper limits of the reported errors could be rather attributed to uncertainties in the data comparison between in situ and satellite observations than inaccuracies of the satellite retrieval. An inter-comparison with the standard Moderate-resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature product exhibits RMSEs and biases in the range of 0.6 to 0.9 and −0.5 to 0.2 K, respectively. The cross-platform consistency of the retrieval was found to be within ~ 0.3 K. For one lake, the satellite-derived trend was compared with the trend of in situ measurements and both were found to be similar. Thus, orbital drift is not causing artificial temperature trends in the data set. A comparison with LSWT derived through global sea surface temperature (SST) algorithms shows lower RMSEs and biases for the simulation-based approach. A running project will apply the developed method to retrieve LSWT for all of Europe to derive the climate signal of the last 30 years. The data are available at doi:10.1594/PANGAEA.831007.

Automated soldier medical readiness: Prevalence of " medically not ready" using data from the electronic soldier readiness processing system (ESRP)

Identifying accurate numbers of soldiers determined to be medically not ready after completing soldier readiness processing may help inform Army leadership about ongoing pressures on the military involved in long conflict with regular deployment. In Army soldiers screened using the SRP checklist for deployment, what is the prevalence of soldiers determined to be medically not ready? Study group. 15,289 soldiers screened at all 25 Army deployment platform sites with the eSRP checklist over a 4-month period (June 20, 2009 to October 20, 2009). The data included for analysis included age, rank, component, gender and final deployment medical readiness status from MEDPROS database. Methods.^ This information was compiled and univariate analysis using chi-square was conducted for each of the key variables by medical readiness status. Results. Descriptive epidemiology Of the total sample 1548 (9.7%) were female and 14319 (90.2%) were male. Enlisted soldiers made up 13,543 (88.6%) of the sample and officers 1,746 (11.4%). In the sample, 1533 (10.0%) were soldiers over the age of 40 and 13756 (90.0%) were age 18-40. Reserve, National Guard and Active Duty made up 1,931 (12.6%), 2,942 (19.2%) and 10,416 (68.1%) respectively. Univariate analysis. Overall 1226 (8.0%) of the soldiers screened were determined to be medically not ready for deployment. Biggest predictive factor was female gender OR (2.8; 2.57-3.28) p<0.001. Followed by enlisted rank OR (2.01; 1.60-2.53) p<0.001. Reserve component OR (1.33; 1.16-1.53) p<0.001 and Guard OR (0.37; 0.30-0.46) p<0.001. For age > 40 demonstrated OR (1.2; 1.09-1.50) p<0.003. Overall the results underscore there may be key demographic groups relating to medical readiness that can be targeted with programs and funding to improve overall military medical readiness.^

Global distributions of picophytoplankton abundance and biomass - Gridded data product (NetCDF) - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

The smallest marine phytoplankton, collectively termed picophytoplankton, have been routinely enumerated by flow cytometry since the late 1980s, during cruises throughout most of the world ocean. We compiled a database of 40,946 data points, with separate abundance entries for Prochlorococcus, Synechococcus and picoeukaryotes. We use average conversion factors for each of the three groups to convert the abundance data to carbon biomass. After gridding with 1° spacing, the database covers 2.4% of the ocean surface area, with the best data coverage in the North Atlantic, the South Pacific and North Indian basins. The average picophytoplankton biomass is 12 ± 22 µg C L-1 or 1.9 g C m-2. We estimate a total global picophytoplankton biomass, excluding N2-fixers, of 0.53 - 0.74 Pg C (17 - 39 % Prochlorococcus, 12 - 15 % Synechococcus and 49 - 69 % picoeukaryotes). Future efforts in this area of research should focus on reporting calibrated cell size, and collecting data in undersampled regions.