A5067074630- Precipitation Measurement and Analysis
- Meteorological Phenomena and Simulations
- Soil Moisture and Remote Sensing
- Climate variability and models
- Cryospheric studies and observations
- Oceanographic and Atmospheric Processes
- Ionosphere and magnetosphere dynamics
- Satellite Communication Systems
- Spacecraft Design and Technology
- Hydrological Forecasting Using AI
- Climate change and permafrost
- Landslides and related hazards
- Viral Infections and Vectors
- Climate change impacts on agriculture
- Hydrology and Watershed Management Studies
- Geophysics and Gravity Measurements
- Arctic and Antarctic ice dynamics
- GNSS positioning and interference
- Plant Water Relations and Carbon Dynamics
- Marine and coastal ecosystems
- Ocean Waves and Remote Sensing
- Radio Wave Propagation Studies
- Geomagnetism and Paleomagnetism Studies
- Fire effects on ecosystems
- earthquake and tectonic studies
Irvine University
2017-2025
University of California, Irvine
2017-2025
UC Irvine Health
2021-2024
Los Alamos National Laboratory
2024
Université Toulouse III - Paul Sabatier
2014-2018
Centre National de la Recherche Scientifique
2014-2018
Institut de Recherche pour le Développement
2014-2018
Université de Toulouse
2016-2018
Laboratoire d’Études en Géophysique et Océanographie Spatiales
2014-2018
Colorado State University
2018
Climate-driven changes in precipitation amounts and their seasonal variability are expected many continental-scale regions during the remainder of 21st century. However, much less is known about future predictability precipitation, an important earth system property relevant for climate adaptation. Here, on basis CMIP6 models that capture present-day teleconnections between previous-season sea surface temperature (SST), we show change to alter SST-precipitation relationships thus our ability...
Abstract. The Goddard Profiling Algorithm (GPROF) is used operationally for the retrieval of surface precipitation and hydrometeor profiles from passive microwave (PMW) observations Global Precipitation Measurement (GPM) mission. Recent updates have led to GPROF V7, which has entered operational use in May 2022. In parallel, development underway improve by transitioning a neural-network-based algorithm called GPROF-NN. This study validates retrievals liquid over snow-free non-mountainous...
Uncertainty quantification is an important component of satellite-derived precipitation products, yet most current methodologies lack the ability to provide such estimates. Here we use a  generative diffusion model produce probabilistic ensembles intensity maps at 1-hour 5-km resolution, conditional on infrared and microwave radiometric measurements from GOES DMSP satellites. The trained with merged ground radar gauge data over southeastern United States. We show that generated...
Abstract The constellation of spaceborne passive microwave (MW) sensors, coordinated under the framework Precipitation Measurement Missions international agreement, continuously produces observations clouds and precipitation all over globe. Goddard profiling algorithm (GPROF) is designed to infer instantaneous surface rate from measured MW radiances. last version (GPROF-2014)—the product more than 20 years algorithmic development, validation, improvement—is currently used estimate rates...
The Madden-Julian Oscillation (MJO) is the leading mode of intra-seasonal climate variability, having profound impacts on a wide range weather and phenomena. Here, we use wavelet-based spectral Principal Component Analysis (wsPCA) to evaluate skill 20 state-of-the-art CMIP6 models in capturing magnitude dynamics MJO. By construction, wsPCA has ability focus desired frequencies capture each propagative physical with one principal component (PC). We show that MJO contribution total variability...
Abstract Observations of clouds and precipitation in the microwave domain from active dual-frequency radar (DPR) passive Global Precipitation Measurement (GPM) Microwave Imager (GMI) onboard GPM Core Observatory satellite are used synergy with cloud tracking information derived infrared imagery GOES-13 Meteosat-7 geostationary satellites for analysis life cycle precipitating systems, terms temporal evolution their macrophysical characteristics, several oceanic continental regions tropics....
Abstract Validation studies have assessed the accuracy of satellite-based precipitation estimates at coarse scale (1° and 1 day or coarser) in tropics, but little is known about their ability to capture finescale variability precipitation. Rain detection masks derived from four multisatellite passive sensor products [Tropical Amount Precipitation with an Estimate Errors (TAPEER), PERSIANN-CCS, CMORPH, GSMaP] are evaluated against ground radar data Burkina Faso. The multiscale evaluation...
Abstract A fully global satellite-based precipitation estimate that can transition across changing Earth surface and complex land/water conditions is an important capability for many hydrological applications, independent evaluation of the derived from weather climate models. This inherently challenging owing to complexity geophysical properties upon which instruments view. To date, these satellite observations originate primarily a variety wide-swath passive microwave (MW) imagers sounders....
Abstract Understanding the nature and origin of errors in satellite precipitation products is important for applications product improvement. Here we propose a new error decomposition scheme incorporating event (continuous rainy periods) information to characterize errors. Under this framework, are attributed inaccuracies occurrence, timing (event start/end time), intensity. The Integrated MultisatellitE Retrieval Global Precipitation Measurement (IMERG) used as our test apply method over...
recipitation exhibits a large variability over wide range of space and time scales: from seconds to years decades in the millimeter scale microphysical processes regional global scales space.It also magnitude frequency, low extremes resulting prolonged droughts high devastating floods.Improving precipitation estimation prediction has great societal impact for decision support water resources management, infrastructure protection design under accelerating climate extremes, quantifying energy...
Wildland fire-atmosphere interaction generates complex turbulence patterns, organized across multiple scales, which inform fire-spread behaviour, firebrand transport, and smoke dispersion. Here, we utilize wavelet-based techniques to explore the characteristic temporal scales associated with coherent patterns in measured temperature turbulent fluxes during a prescribed wind-driven (heading) surface fire beneath forest canopy. We use velocity measurements from tower-mounted sonic anemometers...
Satellite estimation of accumulated precipitation is an important facet the study tropical water cycle. An advanced data merging approach using infrared geostationary imagery and microwave constellation based instantaneous rain rate estimates has been implemented in framework Megha‐Tropiques Global Precipitation Measurements missions. The Tropical Amount Rainfall with Estimation ERors (TAPEER) algorithm tailored to account for loss MADRAS conical scanning radiometer by SAPHIR sounder...
Abstract As more global satellite-derived precipitation products become available, it is imperative to evaluate them carefully for providing guidance as how well space-time features are captured use in hydrologic modeling, climate studies and other applications. Here we propose a Fourier spectral analysis define suite of metrics which the spatial organization storm systems, propagation speed direction features, scales at satellite product reproduces variability reference “ground-truth”...
Abstract Spatiotemporal rainfall variability is a key parameter controlling the dynamics of mosquitoes/vector-borne diseases such as malaria, Rift Valley fever (RVF), or dengue. Impacts from heterogeneity at small scales (i.e., 1–10 km) on risk epidemics host bite rate number bites per and night) must be thoroughly evaluated. A model with hydrological entomological components for prediction RVF zoonosis proposed. The predicts production two mosquito species within 45 km × area in Ferlo...
The scattering of microwaves at frequencies between 50 and 200 GHz by ice particles in the atmosphere is an essential element retrieval instantaneous surface precipitation from spaceborne passive radiometers. This paper explores how variable distribution solid liquid hydrometeors atmospheric column over land surfaces affects brightness temperature (TB) measured GMI 89 through analysis Dual-Frequency Precipitation Radar (DPR) reflectivity profiles along 89-GHz beam. objective to refine...
Spectral PCA (sPCA), in contrast to classical PCA, offers the advantage of identifying organized spatio-temporal patterns within specific frequency bands and extracting dynamical modes. However, unavoidable tradeoff between resolution robustness PCs leads high sensitivity noise overfitting, which limits interpretation sPCA results. We propose herein a simple non-parametric implementation using continuous analytic Morlet wavelet as robust estimator cross-spectral matrices with good...
The use of deep-learning algorithms for estimating the value geophysical variables from remotely-sensed information is rapidly expanding. typical objective function minimized in such mean square error (MSE), which known to lead smooth estimates with compressed dynamical range as compared true distribution variable interest. Here we introduce and evaluate alternative functions, focusing on retrieval precipitation rates satellite passive microwave radiometric measurements using a deep...
Abstract The quantitative estimation of precipitation from orbiting passive microwave imagers has been performed for more than 30 years. development retrieval methods consists establishing physical or statistical relationships between the brightness temperatures (TBs) measured at frequencies 5 and 200 GHz precipitation. Until now, these have essentially established “pixel” level, associating average rate inside a predefined area (the pixel) to collocated multispectral radiometric...
Abstract Satellite precipitation products, as all quantitative estimates, come with some inherent degree of uncertainty. To associate a value the uncertainty to each individual estimate, error modeling is necessary. Most models proposed so far compute function intensity only, and only at one specific spatiotemporal scale. We propose spectral model that accounts for neighboring space–time dynamics into quantification. Systematic distortions signal random errors are characterized distinctively...
In this work, we propose a method to generate an ensemble of equiprobable fields rain occurrence at high resolution (1°/16 and 30 min) using satellite observational constraint. Satellite observations are used constrain the spatio‐temporal variations precipitation fraction various scales. Spatio‐temporal averages scales coarser than 1° 8 h deterministically derived from observations. At finer scales, partially stochastically generated by perturbation wavelet coefficients obtained through...
The feedback of topsoil moisture (SM) content on convective clouds and precipitation is not well understood represented in the current generation coupled cloud physics land-surface models. Here, we use functional decomposition satellite-derived SM (SMAP/L4) vertical profiles (CVP: GPM/DPR/L2A) central US to quantify relationship between distribution water. High-dimensional model representation disentangles contributions other atmospheric variables CVP. Results show sign strength this varies...
A generative diffusion model is used to produce probabilistic ensembles of precipitation intensity maps at the 1-hour 5-km resolution. The generation conditioned on infrared and microwave radiometric measurements from GOES DMSP satellites trained with merged ground radar gauge data over southeastern United States. generated reproduce spatial autocovariance other multiscale statistical properties gauge-radar reference fields average. Conditioning satellite allows us constrain magnitude...