From dust till drowned: the Holocene landscape development at Norderney, East Frisian Islands

Within the multidisciplinary WASA project, 160 cores up to 5 m long have been obtained from the back-barrier area and off the coast of the East Frisian island of Norderney. Thirty-seven contained basal peats on top of Pleistocene sands of the former Geest and 10 of them also had intercalated peats. Based on 100 acclerator mass spectrometry (AMS) 14C dates and analyses of botanical as well as zoological remains from the peats, lagoonal sediments and the underlying sands, a variety of distinct habitats have been reconstructed. On the relatively steep slopes north of the present island, a swampy vegetation fringe several kilometres wide with carrs of alder (Alnus glutinosa) moved in front of the rising sea upwards of the Geest as it existed then until roughly 6 ka, when the sea level reached the current back-barrier region of Norderney at around −6 m NHN (German ordnance datum). From then on for nearly 4000 years a changing landscape with a mosaic of freshwater lakes and fens existed within this area. It was characterised by various stands of Cladium mariscus (fen sedge), alternating with brackish reed beds with Phragmites australis (common reed) and salt meadows with Aster tripolium (sea aster), Triglochin maritima (sea arrowgrass), Juncus gerardii (saltmarsh rush) as well as mudflats with Salicornia europaea (common glasswort). As far as shown by our cores, this highly diverse, and for humans potentially attractive landscape was at least some 4 km wide and followed the coast for about 10 km. Before the rising sea caused diversification of habitats, wet heath as well as dry and dusty sand areas existed. In the course of time, parts of the wet heath turned into raised Sphagnum bogs under an oceanic precipitation regime before this diverse landscape was drowned by the rising sea and finally covered by marine sediments, while the earlier sediments and peats were partly eroded and redeposited.

Characterization of shallow oceanic precipitation using profiling and scanning radar observations at the Eastern North Atlantic ARM observatory

Shallow oceanic precipitation variability is documented using three second-generation radar systems located at the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic observatory: ARM zenith radar (KAZR2), the Ka-band scanning ARM cloud radar (KaSACR2) and the X-band scanning ARM precipitation radar (XSAPR2). First, the radar systems and measurement post-processing techniques, including sea-clutter removal and calibration against colocated disdrometer and Global Precipitation Mission (GPM) observations are described. Then, we present how a combination of profiling radar and lidar observations can be used to estimate adaptive (in both time and height) parameters that relate radar reflectivity (Z) to precipitation rate (R) in the form Z=αRβ, which we use to estimate precipitation rate over the domain observed by XSAPR2. Furthermore, constant altitude plan position indicator (CAPPI) gridded XSAPR2 precipitation rate maps are also constructed. Hourly precipitation rate statistics estimated from the three radar systems differ because KAZR2 is more sensitive to shallow virga and XSAPR2 suffers from less attenuation than KaSACR2 and as such is best suited for characterizing intermittent and mesoscale-organized precipitation. Further analysis reveals that precipitation rate statistics obtained by averaging 12 h of KAZR2 observations can be used to approximate that of a 40 km radius domain averaged over similar time periods. However, it was determined that KAZR2 is unsuitable for characterizing domain-averaged precipitation rate over shorter periods. But even more fundamentally, these results suggest that these observations cannot produce an objective domain precipitation estimate and that the simultaneous use of forward simulators is desirable to guide model evaluation studies.

The sensitivity of oceanic precipitation to sea surface temperature

Our study forms the oceanic counterpart to numerous observational studies over land concerning the sensitivity of extreme precipitation to a change in air temperature. We explore the sensitivity of oceanic precipitation to changing sea surface temperature (SST) by exploiting two novel datasets at high resolution. First, we use the Ocean Rainfall And Ice-phase precipitation measurement Network (OceanRAIN) as an observational along-track shipboard dataset at 1 min resolution. Second, we exploit the most recent European Reanalysis version 5 (ERA5) at hourly resolution on a 31 km grid. Matched with each other, ERA5 vertical velocity allows the constraint of the OceanRAIN precipitation. Despite the inhomogeneous sampling along ship tracks, OceanRAIN agrees with ERA5 on the average latitudinal distribution of precipitation with fairly good seasonal sampling. However, the 99th percentile of OceanRAIN precipitation follows a super Clausius–Clapeyron scaling with a SST that exceeds 8.5 % K−1 while ERA5 precipitation scales with 4.5 % K−1. The sensitivity decreases towards lower precipitation percentiles, while OceanRAIN keeps an almost constant offset to ERA5 due to higher spatial resolution and temporal sampling. Unlike over land, we find no evidence for a decreasing precipitation event duration with increasing SST. ERA5 precipitation reaches a local minimum at about 26 ∘C that vanishes when constraining vertical velocity to strongly rising motion and excluding areas of weak correlation between precipitation and vertical velocity. This indicates that instead of moisture limitations as over land, circulation dynamics rather limit precipitation formation over the ocean. For the strongest rising motion, precipitation scaling converges to a constant value at all precipitation percentiles. Overall, high resolutions in observations and climate models are key to understanding and predicting the sensitivity of oceanic precipitation extremes to a change in SST.

Characterization of Shallow Oceanic Precipitation using Profiling and Scanning Radar Observations at the Eastern North Atlantic ARM Observatory

Shallow oceanic precipitation variability is documented using 2nd generation radars located at the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic observatory: the Ka-band ARM zenith radar (KAZR2), the Ka-band scanning ARM cloud radar (KaSACR2) and the X-band scanning ARM precipitation radar (XSAPR2). First, the radars and measurement post-processing techniques, including sea clutter removal and calibration against collocated disdrometer and Global Precipitation Mission (GPM) observations are described. Then, we present how a combination of profiling radar and lidar observations can be used to estimate adaptive (in both time and height) parameters that relate radar reflectivity (Z) to precipitation rate (R) in the form Z = αRβ which we use to estimate precipitation rate over the domain observed by XSAPR2. Furthermore, Constant Altitude Plan Position Indicator (CAPPI) gridded XSAPR2 precipitation rate maps are also constructed. Hourly precipitation rate statistics estimated from the three radars differ; that is because KAZR2 is more sensitive to shallow virga and because XSAPR2 suffers from less attenuation that KaSACR2 and as such is best suited to characterize intermittent and mesoscale-organized precipitation. Further analysis reveals that precipitation rate statistics obtained by averaging 12 h of KAZR2 observations can be used to approximate that of a domain of 2500 km2 averaged over similar time periods. However, it was determined that KAZR2 is unsuitable to characterize domain average precipitation rate over shorter periods. But even more fundamentally, these results suggest that observations cannot produce objective domain precipitation estimate and that forward-simulators should be used to guide high temporal-resolution model evaluation studies.

On the sensitivity of oceanic precipitation to sea surface temperature

Our study forms the oceanic counterpart to numerous observational studies over land considering the sensitivity of extreme precipitation to a change in air temperature. We explore the sensitivity of oceanic precipitation to changing sea surface temperature (SST) by exploiting two novel datasets at high resolution. First, we use the Ocean Rainfall And Ice-phase precipitation measurement Network (OceanRAIN) as an observational along-track shipboard dataset at 1-minute resolution. Second, we exploit the most recent European Re-Analysis version 5 (ERA5) at hourly resolution on 31 km grid. Matched with each other, ERA5 vertical velocity allows to constrain OceanRAIN precipitation. Despite the inhomogeneous sampling along ship tracks, OceanRAIN agrees with ERA5 on the average latitudinal distribution of precipitation with fairly good seasonal sampling. However, the 99th percentile of OceanRAIN precipitation follows a super-Clausius-Clapeyron scaling with SST that exceeds 8.5 % K−1 while ERA5 precipitation scales with 4.5 % K−1. The sensitivity decreases towards lower precipitation percentiles while OceanRAIN keeps an almost constant offset to ERA5 due to higher spatial resolution and temporal sampling. Unlike over land, we find no evidence for decreasing precipitation event duration with SST. ERA5 precipitation reaches a local minimum at about 26 °C that vanishes when constraining vertical velocity to strongly rising motion and excluding areas of weak correlation between precipitation and vertical velocity. This indicates that instead of moisture limitations as over land, circulation dynamics rather limit precipitation formation over the ocean. For strongest rising motion, precipitation scaling converges to a constant value at all precipitation percentiles. Overall, high resolution in observations as well as climate models is key to understand and predict the sensitivity of oceanic precipitation extremes to a change in SST.

Estimates of the Change in the Oceanic Precipitation Off the Coast of Europe due to Increasing Greenhouse Gas Emissions

This paper presents a consensus estimate of the changes in oceanic precipitation off the coast of Europe under increasing greenhouse gas emissions. An ensemble of regional climate models (RCMs) and three gauge and satellite-derived observational precipitation datasets are compared. While the fit between the RCMs’ simulation of current climate and the observations shows the consistency of the future-climate projections, uncertainties in both the models and the measurements need to be considered to generate a consensus estimate of the potential changes. Since oceanic precipitation is one of the factors affecting the thermohaline circulation, the feedback mechanisms of the changes in the net influx of freshwater from precipitation are relevant not only for improving oceanic-atmospheric coupled models but also to ascertain the climate signal in a global warming scenario.