Andrea Santos-Garcia

Investigation of rain effects on Aquarius Sea Surface Salinity measurements

The Aquarius/SAC-D mission has been providing Sea Surface Salinity (SSS), globally over the ocean, for almost 3 years. As a member of the AQ/SAC-D Cal/Val team, the Central Florida Remote Sensing Laboratory has analyzed these salinity retrievals in the presence of rain and has noted the strong correlation between the spatial patterns of reduced SSS and the spatial distribution of rainfall. It was determined that this is the result of a cause and effect relationship, as opposed to SSS measurement errors. Hence, it is important to understand these SSS changes due to seawater dilution by rain and the associated near-surface salinity stratification. This paper addresses the effects of rainfall on the Aquarius (AQ) SSS retrieval using a macro-scale Rain Impact Model (RIM) in the region of high convective rain over the Inter-tropical Convergence Zone. This model, based on the superposition of a one-dimension eddy diffusion (turbulent diffusion) model, relates sea surface salinity to depth, rain accumulation and time since rainfall. For aiding in the identification of instantaneous and prior rainfall accumulations, an AQ Rain Accumulation product was developed. This product, based on the NOAA CMORPH rain data set, provides the rainfall history for 24 h prior to the observation time, which is integrated over each AQ SSS measurement cell. In this paper results of the RIM validation are presented by comparing AQ measured and RIM simulated SSS for several months of 2012. Results show the high cross correlation for these comparisons and also with the corresponding SSS anomalies relative to HYCOM.

Rain-Induced Near Surface Salinity Stratification and Rain Roughness Correction for Aquarius SSS Retrieval

The effect of rain on surface salinity stratification is analyzed to develop a rain roughness correction scheme to reduce the uncertainty of Aquarius sea surface salinity (SSS) retrieved under rainy conditions. Rain freshwater inputs may cause large discrepancies in salinity measured by Aquarius at 1-2 cm within the surface and the calibration reference SSS from HYCOM (SSSHYCOM) a few meters below the surface. We used the rain impact model (RIM) to adjust SSSHYCOM to reflect near surface salinity stratification caused by freshwater inputs accumulated from rain events that occurred over the past 24 h before Aquarius measurements (SSSRIM). When calibrated with SSSRIM, the residuals, i.e., the difference between measured and model predicted brightness temperature TB, are considered as rain-induced roughness. It was found that rain-induced roughness is larger at lower wind speeds, and decreases as wind increases. The Combined Active Passive algorithm is used to retrieve SSS with (SSSCAP_RC) or without (SSSCAP) rain roughness correction. We find that the simultaneously retrieved wind speed with rain roughness correction has significantly improved agreement with the NCEP wind speed with the rain-dependent bias reduced, self-justifying our rain correction approach. SSS retrieved is validated with salinity measured by drifters at a depth of 45 cm. The difference between satellite retrieved and in situ salinity increases with rain rate. With rain-induced roughness accounted for, the difference between satellite retrieval and drifter increases with rain rate with slope of -0.184 psu (mm h-1)-1, representing the salinity stratification between the two depths (1-2 cm versus 45 cm).

Radiometric intercalibration of the Microwave Humidity Sounder on NOAA-18, MetOp-A, and NOAA-19 using SAPHIR on Megha-Tropiques

The purpose of this paper is to ascertain the use of SAPHIR (in a low earth orbit) for radiometric brightness temperature, Tb, intercalibration of sounder channel sensors (in near polar orbits) within the context of the Global Precipitation Measurement (GPM) mission [1]. For this purpose, we present results of the radiometric intercalibration based on the double differences technique between SAPHIR and the Microwave Humidity Sounder (MHS) on the MetoOp-A, NOAA-18 and NOAA-19 polar orbiting satellites. The analysis presented was reported at the last intercalibration meeting at Toulouse, France, and were performed by Texas A&M University (TAMU), Science Systems and Applications (SSA) and, Central Florida Remote Sensing Lab (CFRSL) at University of Central Florida.

A Roughness Correction for Aquarius Sea Surface Salinity Using the CONAE MicroWave Radiometer

Aquarius (AQ)/SAC-D is a joint National Aeronautics and Space Administration (NASA)/Comisión Nacional de Actividades Espaciales (CONAE; Argentine Space Agency) Earth Sciences satellite mission to measure global sea surface salinity (SSS), using a L-band radiometer/scatterometer that measures ocean brightness temperature (Tb) and radar backscatter (sigma-0). The application of L-band radiometry to retrieve SSS is a difficult task; therefore, precise Tb corrections are necessary to obtain accurate measurements. One of the major error sources is the effect of ocean roughness that “warms” the ocean Tb. The baseline approach, to provide this ocean roughness correction, uses the AQ radar scatterometer measurement of ocean sigma-0 to infer the radiometric excess ocean emissivity. In contrast, this paper develops an alternate approach for the AQ ocean roughness correction using the MicroWave Radiometer (MWR) Tb measurements at Ka-band. The theoretical basis of this MWR ocean roughness correction algorithm is described, which translates these Ka-band measurements to L-band to remove the AQ Tb errors that are caused by ocean wind speed and direction. MWR ocean roughness correction results are compared with corresponding results from the AQ scatterometer method. Also, AQ SSS retrievals are presented using both sets of roughness corrections that demonstrate the relative effectiveness of the MWR and AQ scatterometer approaches.

Aquarius/SAC-D Microwave Radiometer brightness temperature validation

The Microwave Radiometer (MWR) on-board Aquarius/SAC-D is part of a joint international science mission between the National Aeronautics and Space Administration (NASA) and the Argentine Space Agency (Comision Nacional de Actividades Espaciales, CONAE). MWR, developed by CONAE, is a three channel Dicke radiometer operating at 23.8 GHz H-Pol and 36.5 GHz V-& H-Pol. This instrument complements the prime sensor, Aquarius L-band radiometer/scatterometer, by providing simultaneous spatially collocated environmental measurements such as integrated atmospheric water vapor, ocean surface wind speed, oceanic rain rate, and sea ice concentration, which aid in retrieving accurate Sea Surface Salinity. This paper presents the post-launch brightness temperature (Tb) validation, which was conducted using the CFRSL XCAL approach for inter-satellite radiometric comparison with the US Navys WindSat radiometer during the first 10 months of MWR on-orbit measurements.

Salinity rain impact model (RIM) optimization: Preliminary results

Based upon research with the Aquarius (AQ) satellite remote sensor, a rain impact model (RIM) has been developed which estimates the occurrence of sea surface salinity (SSS) stratification. RIM uses global salinity (HYCOM) and rainfall (CMORPH) products to estimate the transient change in SSS due to rainfall. Previously SSS predicted by RIM have exhibited good correlations with AQ, but the choice for the duration window (24 h) was arbitrary. In this paper, we examine the effect on RIM of different time duration windows.

Measurement of rain-induced oceanic surface salinity stratification using L-band satellite radiometers

This paper presents recent results of an investigation into the transient effects of oceanic rainfall on the profile of near-surface salinity. Based upon research conducted with the NASA/CONAE Aquarius/SAC-D mission, it was determined that the primary rain impact was to dilute the sea surface salinity (SSS), which was accurately captured by the Aquarius (AQ) microwave radiometer/scatterometer observations. As a result, CFRSL has developed a rain impact model (RIM) to provide a quality flag for AQ SSS measurements, which alerts the users of the possibility of salinity stratification. RIM uses the ocean community salinity model HYCOM and a NOAA global rainfall product CMORPH to estimate the change in SSS at the time of the satellite observation. While this paper is applicable to all L-band radiometer missions namely, Aquarius, SMOS and SMAP, only results from AQ will be presented herein. An example of near-surface salinity profiles derived from AQ RIM is presented with associated rain events captured by CMORPH.

SMOS Near-Surface Salinity Stratification Under Rainy Conditions

The European Space Agencys Soil Moisture Ocean Salinity (SMOS) satellite was launched in 2009 to measure land soil moisture and sea surface salinity (SSS). It carries an L-band microwave imaging radiometer that measures brightness temperatures that are used to produce global ocean salinity (OS) maps every three days. Similar maps are obtained with NASAs L-band push-broom radiometer Aquarius (AQ) on board of the AQ/SAC-D satellite that was launched in 2011. In previous studies, the Central Florida Remote Sensing Laboratory (CFRSL) has analyzed AQ SSS retrievals during rain and has developed a model to predict the effect of precipitation on the SSS measurements. This rain impact model (RIM) estimates the transient near-surface salinity stratification based upon the corresponding rain accumulation over the previous 24 h to the satellite observation. In this paper, the RIM methodology has been adapted to the SMOS geometry, presenting comparisons with its SSS measurements; also, spatial correlations are performed between SMOS salinity images with those predicted by RIM for different wind speed ranges. Therefore, the main objective of this research is to better understand the processes of near-surface salinity stratification, which impact the interpretation of satellite-based SSS measurements to measure the ocean bulk salinity (5-10-m depth). The results presented in this paper show an excellent performance of RIM when applied to SMOS SSS data. Also, the SSS comparisons show that significant rain events are rapidly diluted for wind speeds of ~ 12 m/s and above.

Near-surface salinity stratification observed by SMOS under rainy conditions

ESAs Soil Moisture Ocean Salinity (SMOS) Earth Explorer mission globally measures ocean salinity every three days with a Microwave Imaging Radiometer using the Aperture Synthesis (MIRAS) radiometer. Also 7-day global ocean salinity measurements are available from NASAs Aquarius (AQ) L-band push-broom radiometer on-board of Aquarius/SAC-D satellite. The Central Florida Remote Sensing Laboratory has analyzed AQ sea surface salinity (SSS) retrievals in the presence of rain and has developed a Rain Impact Model (RIM) that predicts transient near-surface salinity stratification based upon the corresponding rain accumulation over the previous 24 hours. The objective of this paper is to extend this analysis to SMOS and perform spatial correlations between SMOS salinity images with those predicted by RIM. The aim of this work is to better understand the processes of near-surface salinity stratification, which impacts the interpretation of satellite based SSS measurements to measure the ocean bulk salinity (5-10 m depth).

CONAE Microwave Radiometer (MWR) Counts to Tb Algorithm and On-Orbit Validation

The Aquarius/SAC-D, International Earth Science Satellite Mission, is a collaboration between NASA and the Argentine Space Agency (Comisión Nacional de Actividades Espaciales, CONAE) that was launched on June 10, 2011 to provide scientists with monthly global maps of sea surface salinity (SSS) to understand the Earths hydrological cycle and to investigate global climate change. This paper concerns the microwave radiometer (MWR), a CONAE science instrument developed to provide simultaneous and spatially collocated environmental measurements that complement the prime L-band radiometer/scatterometer sensor (Aquarius) for measuring SSS. MWR is a 3-channel (23.8-GHz H-pol and 36.5-GHz V- and H-pol) passive microwave instrument that measures the Earths brightness temperature (Tb). This paper describes the MWR counts to Tb algorithm (V6.0) and presents results of the on-orbit Tb validation using intersatellite radiometric calibration with the Naval Research Laboratorys WindSat (WS) satellite radiometer. In addition, an alternative MWR counts to Tb algorithm (V7.0) is presented that normalizes the MWR Tbs to WS. This latter version (V7.0) has the advantage of removing MWR time-varying radiometric calibration biases between antenna beams and channels as verified by on-orbit comparisons with WS.