Satellite Perspectives of Sea Surface Temperature Diurnal Warming on Atmospheric Moistening and Radiative Heating During MJO

Diurnal air-sea coupling affects climate modes such as the Madden-Julian Oscillation (MJO) via the regional moist static energy budget. Prior to MJO initiation, large-scale subsidence increases (decreases) surface shortwave insolation (winds). These act in concert to significantly warm the uppermost layer of the ocean over the course of a single day and the ocean mixed layer over the course of 1-2 weeks. Here, we provide an integrated analysis of multiple surface, top-of-atmosphere, and atmospheric column observations to assess the covariability related to regions of strong diurnal sea surface temperature (dSST) warming over 44 MJO events between 2000-2018 to assess their role in MJO initiation. Combining satellite observations of evaporation and precipitation with reanalysis moisture budget terms, we find 30-50% enhanced moistening over high dSST regions during late afternoon using either ERA5 or MERRA-2 despite large model biases. Diurnally developing moisture convergence, only modestly weaker evaporation, and diurnal minimum precipitation act to locally enhance moistening over broad regions of enhanced diurnal warming, which rectifies onto the larger scale. Field campaign ship and sounding data corroborate that strong dSST periods are associated with reduced middle tropospheric humidity and larger diurnal amplitudes of surface warming, evaporation, instability, and column moistening. Further, we find greater daytime increases in low cloud cover and evidence of enhanced radiative destabilization for the top 50th dSST percentile. Together, these results support that dSST warming acts in concert with large-scale dynamics to enhance moist static energy during the suppressed to active phase transition of the MJO.

Assessment of Extreme Diurnal Warming in Operational Geosynchronous Satellite Sea Surface Temperature Products

We evaluate the reliability and basic characteristics of observations of extreme DW events from current operational geostationary satellite sea surface temperature (SST) products through examination of three months of diurnal warming (DW) estimates derived by different methodologies from the Spinning Enhanced Visible and Infrared Imager on Meteosat-11, Advanced Himawari Imager on Himawari-8, and Advanced Baseline Imager on the Geostationary Operational Environmental Satellite (GOES)-16. This work primarily focuses on the following research questions: (1) Can these operational SST products accurately characterize extreme DW events? (2) What are the amplitudes and frequencies of these events? To answer these, we compute distributions of DW and DW exceedance and compare them amongst the different methods and geostationary sensors. Examination of the DW estimates demonstrates several challenges in accurately deriving distributions of the DW amplitude, particularly associated with estimating the “foundation” temperature and uncertainties in cloud screening. Overall, the results suggest that current geostationary sensors can reliably assess extreme DW, but the estimates are sensitive to the computational methods applied. We thus suggest careful processing/screening of the SST retrievals. We find a value of 3 K, corresponding to the 99th percentile, provides a potential practical threshold for extreme warming, but events of at least 6 K were reliably observed. Warming in excess of 6 K occurred somewhere an average of 47% of the time, and its probability at a given location was of O(10−6).

Saildrone: Adaptively Sampling the Marine Environment

From 11 April to 11 June 2018 a new type of ocean observing platform, the Saildrone surface vehicle, collected data on a round-trip, 60-day cruise from San Francisco Bay, down the U.S. and Mexican coast to Guadalupe Island. The cruise track was selected to optimize the science team’s validation and science objectives. The validation objectives include establishing the accuracy of these new measurements. The scientific objectives include validation of satellite-derived fluxes, sea surface temperatures, and wind vectors and studies of upwelling dynamics, river plumes, air–sea interactions including frontal regions, and diurnal warming regions. On this deployment, the Saildrone carried 16 atmospheric and oceanographic sensors. Future planned cruises (with open data policies) are focused on improving our understanding of air–sea fluxes in the Arctic Ocean and around North Brazil Current rings.

Comparison of Himawari-8 AHI SST with Shipboard Skin SST Measurements in the Australian Region

Sea surface temperature (SST) measurements from the geostationary satellite Himawari-8 Advanced Himawari Imager (AHI) are compared with in situ skin SSTs derived from shipboard Infrared SST Autonomous Radiometers (ISAR) in the Australian region. The mean bias and standard deviation of the differences between Himawari-8 AHI and ISAR skin SST of best quality are 0.09 K and 0.30 K, with total matchups numbering 2701. Shipboard bulk SST measurements at depths between around 7.1 and 9.9 meters are compared with the matchups in a case study. Analyses show significant differences between skin and bulk SST measurements of maximum value 2.23 K under conditions of high diurnal warming. The results also demonstrate that Himawari-8 AHI skin SST with high temporal resolution has the ability to accurately measure diurnal warming events.

Nighttime Cool Skin Effect Observed from Infrared SST Autonomous Radiometer (ISAR) and Depth Temperatures

The nighttime ocean cool skin signal ΔT [defined as skin sea surface temperature (SSTskin) minus depth SST (SSTdepth)] is investigated using 103 days of matchups between shipborne Infrared SST Autonomous Radiometer (ISAR) SSTskin and water intake SSTdepth at ~7.1–9.9-m depths, in oceans around Australia. Before data analysis, strict quality control of ISAR SSTskin data is conducted and possible diurnal warming contamination is carefully minimized. The statistical distribution of ΔT, and its dependencies on wind speed, heat flux, etc., are consistent with previous findings. The overall average ΔT value is −0.23 K. It is observed that the magnitude of the cool skin signal increases after midnight and a coolest skin offset (with an average value of −0.36 K) is found at around dawn. The dependency of ΔT on SST conditions is observed. Direct warm skin events are discovered when the net heat flux direction is from the atmosphere to the ocean, which is more likely to occur at high latitudes when the air is very humid and warmer than the SST. In addition, several cool skin models are validated: one widely used physical model performs best and can capture most skin-effect trends and details; the empirical models only reflect the basic features of the observed ΔT values. If the user cannot apply the physical model (due to, e.g., the algorithm complexity or missing inputs), then the empirical parameterization in the form proposed in a 2002 study can be used. However, we recommend using a new set of parameters, calculated in this study, based on much more representative dataset, and with more rigorous quality control.