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

Simulation of ship-track versus satellite-sensor differences in oceanic precipitation using an island-based radar

The point-to-area problem strongly complicates the validation of satellite-based precipitation estimates, using surface-based point measurements. We simulate the limited spatial representation of light to moderate oceanic precipitation rates along ship tracks with respect to areal passive microwave satellite estimates using data from a subtropical island-based radar. The radar data serves to estimate the discrepancy between point-like and areal precipitation measurements. From the spatial discrepancy, two statistical adjustments are derived so that along-track precipitation ship data better represents areal precipitation estimates from satellite sensors. The first statistical adjustment uses the average duration of a precipitation event as seen along a ship track and the second adjustment uses the median-normalized along-track precipitation rate. Both statistical adjustments combined reduce the root mean squared error by 0.24 mm h 10 (55%) compared to the unadjusted average track of 60 radar pixels in length corresponding to a typical ship speed of 24–34 km h depending on track orientation. Beyond along-track averaging, the statistical adjustments represent an important step towards a more accurate validation of precipitation derived from passive microwave satellite sensors using point-like along-track surface precipitation reference data

Anthropogenic intensification of short-duration rainfall extremes

Short- duration (1-3 h) rainfall extremes can cause serious damage to societies through rapidly developing (flash) flooding and are determined by complex, multifaceted processes that are altering as Earth's climate warms. In this Review, we examine evidence from observational, theoretical and modelling studies for the intensification of these rainfall extremes, the drivers and the impact on flash flooding. Both short- duration and long- duration (\textgreater1 day) rainfall extremes are intensifying with warming at a rate consistent with the increase in atmospheric moisture (~7% K-1), while in some regions, increases in short- duration extreme rainfall intensities are stronger than expected from moisture increases alone. These stronger local increases are related to feedbacks in convective clouds, but their exact role is uncertain because of the very small scales involved. Future extreme rainfall intensification is also modulated by changes to temperature stratification and large- scale atmospheric circulation. The latter remains a major source of uncertainty. Intensification of short- duration extremes has likely increased the incidence of flash flooding at local scales and this can further compound with an increase in storm spatial footprint to considerably increase total event rainfall. These findings call for urgent climate change adaptation measures to manage increasing flood risks

An automatic precipitation phase distinction algorithm for optical disdrometer data over the global ocean

The lack of high-quality in situ surface precipitation data over the global ocean so far limits the capability to validate satellite precipitation retrievals. The first systematic ship-based surface precipitation data set OceanRAIN (Ocean Rainfall And Ice-phase precipitation measurement Network) aims at providing a comprehensive statistical basis of in situ precipitation reference data from optical disdrometers at 1 min resolution deployed on various research vessels (RVs). Deriving the precipitation rate for rain and snow requires a priori knowledge of the precipitation phase (PP). Therefore, we present an automatic PP distinction algorithm using available data based on more than 4 years of atmospheric measurements onboard RV Polarstern that covers all climatic regions of the Atlantic Ocean. A time-consuming manual PP distinction within the OceanRAIN post-processing serves as reference, mainly based on 3-hourly present weather information from a human observer. For automation, we find that the combination of air temperature, relative humidity, and 99th percentile of the particle diameter predicts best the PP with respect to the manually determined PP. Excluding mixed phase, this variable combination reaches an accuracy of 91 % when compared to the manually determined PP for 149 635 min of precipitation from RV Polarstern. Including mixed phase (165 632 min), an accuracy of 81.2 % is reached for two independent PP distributions with a slight snow overprediction bias of 0.93. Using two independent PP distributions represents a new method that outperforms the conventional method of using only one PP distribution to statistically derive the PP. The new statistical automatic PP distinction method considerably speeds up the data post-processing within OceanRAIN while introducing an objective PP probability for each PP at 1 min resolution

Towards an along-track validation of HOAPS precipitation using OceanRAIN optical disdrometer data over the Atlantic Ocean

The Hamburg Ocean Atmosphere Parameters and fluxes from Satellite data (HOAPS) passive-microwave precipitation scan product is compared to the Ocean Rainfall And Ice-phase precipitation measurement Network (OceanRAIN) surface-based precipitation reference dataset over the global ocean. For the first time, we apply statistical point-to-area adjustments and along-track averaging to ship-based OceanRAIN precipitation data over the Atlantic Ocean to better represent collocated precipitation rates within a HOAPS satellite pixel. The statistical adjustments strongly reduce the HOAPS–OceanRAIN root-mean-square error from 2.65 mm h−1 to 1.01 mm h−1. Overall, the point-to-area effect stronger impacts HOAPS–OceanRAIN differences than the precipitation regime. Higher-resolved satellite data indicates that these adjustments work best for most convective-like precipitation cases while some rather stratiform-like precipitation cases would need no adjustment. Excluding precipitation rates below the HOAPS sensitivity threshold of 0.3 mm h−1 reduces the difference in average precipitation rates between HOAPS hits and false detections combined and OceanRAIN hits and misses combined to 2 %. This precipitation-rate difference lies below the uncertainty obtained from resampling of about 10 %. Without false detections, the HOAPS precipitation rate of hits-only exceeds that of OceanRAIN by 50 %. Most of the HOAPS false detections follow from cases when precipitation occurs within the HOAPS pixel but off the ship track. Consequently, these apparent false detections lead to an overestimation of HOAPS precipitation rates compared to OceanRAIN, particularly in the inner tropics and partly mid-latitudes where clustered convective precipitation occurs most frequently. Misses cause underestimated HOAPS precipitation rates mainly in the mid- and high-latitudes. However, for a HOAPS validation, apparent false detections need to be considered in addition to hits of OceanRAIN precipitation rates to which we successfully applied statistical point-to-area adjustments

OceanRAIN - The global ocean surface-reference dataset for characterization, validation and evaluation of the water cycle

OceanRAIN—the Ocean Rainfall And Ice-phase precipitation measurement Network—is the first comprehensive in-situ surface-reference dataset comprising all water cycle parameters to meet the requirements of the international scientific teams for high-quality precipitation data over the global oceans. OceanRAIN is aimed at satellite retrieval calibration and product validation of the GPM (Global Precipitation Measurement) era, to improve the representation of precipitation and air-sea interactions in re-analyses and models, and to enhance our understanding of water cycle processes over the global oceans. For this purpose, OceanRAIN version 1.0 provides in-situ data of precipitation, evaporation and the resulting freshwater flux at 1-min resolution from June 2010 to April 2017. More than 6.83 million minutes with 75 parameters from 8 ships cover all routinely measured atmospheric and oceanographic state variables along with those required to derive the turbulent heat fluxes. The precipitation parameter is based on measurements of the optical disdrometer ODM470 specifically designed for all-weather shipboard operations. The occurrence, intensity and accumulation of rain, snow and mixed-phase precipitation are derived from particle size distributions. Additionally, all relevant microphysical precipitation and radar-related parameters are provided

OceanRAIN, a new in-situ shipboard global ocean surface-reference dataset of all water cycle components

OceanRAIN—the Ocean Rainfall And Ice-phase precipitation measurement Network—provides in-situ along-track shipboard data of precipitation, evaporation and the resulting freshwater flux at 1-min resolution over the global oceans from June 2010 to April 2017. More than 6.83 million minutes with 75 parameters from 8 ships cover all routinely measured atmospheric and oceanographic state variables along with those required to derive the turbulent heat fluxes. The precipitation parameter is based on measurements of the optical disdrometer ODM470 specifically designed for all-weather shipboard operations. The rain, snow and mixed-phase precipitation occurrence, intensity and accumulation are derived from particle size distributions. Additionally, microphysical parameters and radar-related parameters are provided. Addressing the need for high-quality in-situ precipitation data over the global oceans, OceanRAIN-1.0 is the first comprehensive along-track in-situ water cycle surface reference dataset for satellite product validation and retrieval calibration of the GPM (Global Precipitation Measurement) era, to improve the representation of precipitation and air-sea interactions in re-analyses and models, and to improve understanding of water cycle processes over the global ocean

Glacial–interglacial changes and Holocene variations in Arabian Sea denitrification

At present, the Arabian Sea has a permanent oxygen minimum zone (OMZ) at water depths between about 100 and 1200 m. Active denitrification in the upper part of the OMZ is recorded by enhanced δ15N values in the sediments. Sediment cores show a δ15N increase during the middle and late Holocene, which is contrary to the trend in the other two regions of water column denitrification in the eastern tropical North and South Pacific. We calculated composite sea surface temperature (SST) and δ15N ratios in time slices of 1000 years of the last 25 kyr to better understand the reasons for the establishment of the Arabian Sea OMZ and its response to changes in the Asian monsoon system. Low δ15N values of 4–7 ‰ during the last glacial maximum (LGM) and stadials (Younger Dryas and Heinrich events) suggest that denitrification was inactive or weak during Pleistocene cold phases, while warm interstadials (ISs) had elevated δ15N. Fast changes in upwelling intensities and OMZ ventilation from the Antarctic were responsible for these strong millennial-scale variations during the glacial. During the entire Holocene δ15N values > 6 ‰ indicate a relatively stable OMZ with enhanced denitrification. The OMZ develops parallel to the strengthening of the SW monsoon and monsoonal upwelling after the LGM. Despite the relatively stable climatic conditions of the Holocene, the δ15N records show regionally different trends in the Arabian Sea. In the upwelling areas in the western part of the basin, δ15N values are lower during the mid-Holocene (4.2–8.2 ka BP) compared to the late Holocene (< 4.2 ka BP) due to stronger ventilation of the OMZ during the period of the most intense southwest monsoonal upwelling. In contrast, δ15N values in the northern and eastern Arabian Sea rose during the last 8 kyr. The displacement of the core of the OMZ from the region of maximum productivity in the western Arabian Sea to its present position in the northeast was established during the middle and late Holocene. This was probably caused by (i) reduced ventilation due to a longer residence time of OMZ waters and (ii) augmented by rising oxygen consumption due to enhanced northeast-monsoon-driven biological productivity. This concurs with the results of the Kiel Climate Model, which show an increase in OMZ volume during the last 9 kyr related to the increasing age of the OMZ water mass