Christian Klepp

Evaluation of HOAPS-3 Ocean Surface Freshwater Flux Components

Abstract Today, latent heat flux and precipitation over the global ocean surface can be determined from microwave satellite data as a basis for estimating the related fields of the ocean surface freshwater flux. The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS) is the only generally available satellite-based dataset with consistently derived global fields of both evaporation and precipitation and hence of freshwater flux for the period 1987–2005. This paper presents a comparison of the evaporation E, precipitation P, and the resulting freshwater flux E − P in HOAPS with recently available reference datasets from reanalysis and other satellite observation projects as well as in situ ship measurements. In addition, the humidity and wind speed input parameters for the evaporation are examined to identify sources for differences between the datasets. Results show that the general climatological patterns are reproduced by all datasets. Global mean time series often agree within abo...

Comparison of HOAPS, QuikSCAT, and Buoy Wind Speed in the Eastern North Atlantic and the North Sea

A systematic investigation and comparison of near-surface marine wind speed obtained from in situ and satellite observations, a reanalysis, and a reanalysis-driven regional climate model (RCM) are presented for the eastern North Atlantic and the North Sea. Wind-speed retrievals from QuikSCAT Level 2B 12.5 km and HOAPS-3-S are analyzed. The root-mean-square error (rmse) between QuikSCAT and buoy 10-m equivalent neutral wind (EQNW) is 1.50 (1.87) m · s-1 using a colocation criteria of 0.1° and 0.06° (0.3° and 0.2°) in longitudinal and latitudinal distances from buoy locations and within 10 (20) min, demonstrating that QuikSCATs mission requirement of providing wind speed with an rmse of 2 m · s-1 is met for the investigated area. The influence of three different stability and anemometer height correction algorithms for buoy wind speed on the buoy/QuikSCAT error is assessed: EQNW gives the best agreement with QuikSCAT data; however, differences are smaller than the buoy measurement error. The rmse between HOAPS and buoy wind converted to 10 m by the logarithmic wind profile is 2.27 (2.36) m · s-1 using a colocation of 0.1° × 0.06° (0.3° × 0.2°) and within 10 (20) min. QuikSCAT shows good agreement with buoy wind for speeds up to 20 m · s-1. HOAPS shows an underestimation of high wind speeds beyond 15-20 m · s-1 probably due to a saturation of the return signal. The rmse between buoy wind speed and the National Centers of Environmental Prediction/National Center for Atmospheric Research Reanalysis (NRA R1) and the spectrally nudged RCM REMO (SN-REMO) are 2.2 and 2.5 m · s-1, respectively.

Validation practices for satellite based earth observation data across communities

Assessing the inherent uncertainties in satellite data products is a challenging task. Different technical approaches have been developed in the Earth Observation (EO) communities to address the validation problem which results in a large variety of methods as well as terminology. This paper reviews state-of-the-art methods of satellite validation and documents their similarities and differences. First, the overall validation objectives and terminologies are specified, followed by a generic mathematical formulation of the validation problem. Metrics currently used as well as more advanced EO validation approaches are introduced thereafter. An outlook on the applicability and requirements of current EO validation approaches and targets is given.

Improvements of satellite-derived cyclonic rainfall over the North Atlantic

Abstract Case studies of rainfall, derived from Special Sensor Microwave Imager (SSM/I) satellite data during the passage of individual cyclones over the North Atlantic, are presented to enhance the knowledge of rainfall processes associated with frontal systems. A multisatellite method is applied for complete coverage of the North Atlantic twice a day. Different SSM/I precipitation algorithms have been tested for individual cyclones and compared to the Global Precipitation Climatology Project (GPCP) datasets. An independent rainfall pattern and intensity validation method is presented using voluntary observing ship (VOS) datasets and Advanced Very High Resolution Radiometer (AVHRR) images. Intense cyclones occur frequently in the wintertime period, with cold fronts propagating far south over the North Atlantic. Following upstream, large cloud clusters are frequently embedded in the cellular structured cold air of the backside regions, which produce heavy convective rainfall events, especially in the regi...

Evaluating light rain from satellite- and ground-based remote sensing data over the subtropical North Atlantic

AbstractThree state-of-the-art satellite climatologies are analyzed for their ability to observe light rain from predominantly shallow, warm clouds over the subtropical North Atlantic Ocean trade winds (1998–2005). HOAPS composite (HOAPS-C), version 3.2; TMPA, version 7; and GPCP 1 Degree Daily (1DD), version 1.2, are compared with ground-based S-Pol radar data from the Rain in Cumulus over the Ocean (RICO; winter 2004/05) campaign and Micro Rain Radar data from the Barbados Cloud Observatory (2010–12). Winter rainfall amounts to one-third of annual rainfall, whereby light rain from warm clouds dominates. Daily rain occurrence and rain intensity during RICO largely differ among the satellite climatologies. TMPA best captures the frequent light rain events, only missing 7% of days on which the S-Pol radar detects rain, whereas HOAPS-C misses 33% and GPCP 1DD misses 56%. Algorithm constraints mainly cause these differences. In HOAPS-C also few available passive microwave (PMW) sensor overpasses limit its pe...

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 represent 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 − 1 (55%) compared to the unadjusted average track of 60 radar pixels in length corresponding to a typical ship speed of 24–34 km h − 1 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.

Satellite derived energy and water cycle components in north atlantic cyclones

Abstract Data from passive microwave satellite instruments are now widely used to derive climatological values of various atmospheric water cycle components. But as the accuracy should also be sufficient for the application of these data to individual cases, such data have been applied to the study of water cycle components in individual North-Atlantic cyclones. The goal was to document the spatial distribution and the temporal development of water cycle components from satellite data and to evaluate their representation in atmospheric models. For the investigation, data from the polar orbiting microwave instrument SSM/I on board the DMSP satellite is used. To get the best spatial coverage and to follow the time development of individual cyclones it was necessary to develop first procedures for the spatial combination of products from several DMSP satellites. The data of one instrument may be used to fill in empty areas from the limited swath of the other without too much overlap problems. This procedure has been applied to the FASTEX-period in January and February 1997 using F10, F11 and F13 satellites. The water cycle parameters derived from the available satellite data for this period show clearly the expected precipitation signatures connected with cold and warm fronts. However we found in many cases large areas with intense rain events in the cold air flow to the west of the cyclone. Comparisons with the rain rate information from the corresponding ECMWF analysis indicate that these convective rain events are vastly underestimated in the ECMWF analysis.

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 oceans.