Lake ice phenology from AVHRR data for European lakes: An automated two-step extraction method

Several lake ice phenology studies from satellite data have been undertaken. However, the availability of long-term lake freeze-thaw-cycles, required to understand this proxy for climate variability and change, is scarce for European lakes. Long time series from space observations are limited to few satellite sensors. Data of the Advanced Very High Resolution Radiometer (AVHRR) are used in account of their unique potential as they offer each day global coverage from the early 1980s expectedly until 2022. An automatic two-step extraction was developed, which makes use of near-infrared reflectance values and thermal infrared derived lake surface water temperatures to extract lake ice phenology dates. In contrast to other studies utilizing thermal infrared, the thresholds are derived from the data itself, making it unnecessary to define arbitrary or lake specific thresholds. Two lakes in the Baltic region and a steppe lake on the Austrian–Hungarian border were selected. The later one was used to test the applicability of the approach to another climatic region for the time period 1990 to 2012. A comparison of the extracted event dates with in situ data provided good agreements of about 10 d mean absolute error. The two-step extraction was found to be applicable for European lakes in different climate regions and could fill existing data gaps in future applications. The extension of the time series to the full AVHRR record length (early 1980 until today) with adequate length for trend estimations would be of interest to assess climate variability and change. Furthermore, the two-step extraction itself is not sensor-specific and could be applied to other sensors with equivalent near- and thermal infrared spectral bands.

Early autonomic dysfunction in patients with diabetes mellitus assessed by spectral analysis of heart rate and blood pressure variability

Patients with diabetes mellitus (DM) often have alterations of the autonomic nervous system (ANS), even early in their disease course. Previous research has not evaluated whether these changes may have consequences on adaptation mechanisms in DM, e.g. to mental stress. We therefore evaluated whether patients with DM who already had early alterations of the ANS reacted with an abnormal regulatory pattern to mental stress. We used the spectral analysis technique, known to be valuable and reliable in the investigation of disturbances of the ANS. We investigated 34 patients with DM without clinical evidence of ANS dysfunction (e.g. orthostatic hypotension) and 44 normal control subjects (NC group). No patients on medication known to alter ANS responses were accepted. The investigation consisted of a resting state evaluation and a mental stress task (BonnDet). In basal values, only the 21 patients with type 2 DM were different in respect to body mass index and systolic blood pressure. In the study parameters we found significantly lower values in resting and mental stress spectral power of mid-frequency band (known to represent predominantly sympathetic influences) and of high-frequency and respiration bands (known to represent parasympathetic influences) in patients with DM (types 1 and 2) compared with NC group (5.3 +/- 1.2 ms2 vs. 6.1 +/- 1.3 ms2, and 5.5 +/- 1.6 ms2 vs. 6.2 +/- 1.5 ms2, and 4.6 +/- 1.7 ms2 vs. 6.2 +/- 1.5 ms2, for resting values respectively; 4.7 +/- 1.4 ms2 vs. 5.9 +/- 1.2 ms2, and 4.6 +/- 1.9 ms2 vs. 5.6 +/- 1.7 ms2, and 3.7 +/- 2.1 ms2 vs. 5.6 +/- 1.7 ms2, for stress values respectively; M/F ratio 6/26 vs. 30/14). These differences remained significant even when controlled for age, sex, and body weight. However, patients with DM type 2 (and significantly higher body weight) showed only significant values in mental stress modulus values. There were no specific group effects in the patients with DM in adaptation mechanisms to mental stress compared with the NC group. These findings demonstrate that power spectral examinations at rest are sufficiently reliable to diagnose early alterations in ANS in patients with DM. The spectral analysis technique is sensitive and reliable in investigation of ANS in patients with DM without clinically symptomatic autonomic dysfunction.