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Applications of Dynamic Land Surface Information for Passive Microwave Precipitation Retrieval, in contrast to the uniform MiRS or GPROF formulations. As a two-step process, with individual OE emissivity retrievals required for each constellation sensor, the hybrid technique is not proposed as an operational scheme but is presented here for use as an enhanced and more observationally based, radiometrically consistent retrieval system for research. In particular, the inclusion of surface emissivity and concurrent retrieved water vapor has many applications for use in the study of land–atmosphere
, in contrast to the uniform MiRS or GPROF formulations. As a two-step process, with individual OE emissivity retrievals required for each constellation sensor, the hybrid technique is not proposed as an operational scheme but is presented here for use as an enhanced and more observationally based, radiometrically consistent retrieval system for research. In particular, the inclusion of surface emissivity and concurrent retrieved water vapor has many applications for use in the study of land–atmosphere
interest, exhibiting a plethora of modes caused by different physical processes (e.g., solar forcing, oceanic/atmospheric circulations, land–atmosphere interactions, etc.), and imprinting themselves at various spatial and temporal scales. The accurate identification and modeling of the modes of the climate system is necessary for many key problems in geosciences, such as weather/climate prediction, attribution of extreme events and hazards, and assessment of climate change impacts. The comprehensive
interest, exhibiting a plethora of modes caused by different physical processes (e.g., solar forcing, oceanic/atmospheric circulations, land–atmosphere interactions, etc.), and imprinting themselves at various spatial and temporal scales. The accurate identification and modeling of the modes of the climate system is necessary for many key problems in geosciences, such as weather/climate prediction, attribution of extreme events and hazards, and assessment of climate change impacts. The comprehensive
; McCabe and Dettinger 1999 ; Dai 2013 ], also exhibit limited predictive skill. The main reason is that the complex and nonstationary interactions between large-scale dynamics and regional hydroclimate cannot be captured sufficiently well with a limited number of prespecified climate indices (regions used for computing sea surface temperature anomalies) as predictors, even when sophisticated statistical schemes are used (nonlinear statistical schemes, Bayesian techniques, etc.). Recognizing the
; McCabe and Dettinger 1999 ; Dai 2013 ], also exhibit limited predictive skill. The main reason is that the complex and nonstationary interactions between large-scale dynamics and regional hydroclimate cannot be captured sufficiently well with a limited number of prespecified climate indices (regions used for computing sea surface temperature anomalies) as predictors, even when sophisticated statistical schemes are used (nonlinear statistical schemes, Bayesian techniques, etc.). Recognizing the
1. Introduction Latent heat release within the atmosphere arises from heat exchanges as water changes phase between vapor, liquid, and solid and is an important component or principal driver for many atmospheric circulations. Even at midlatitudes, latent heating (LH) can be an important part of midlatitude cyclone dynamics and the larger-scale storm track ( Willison et al. 2013 ) and can be especially important for the rapid deepening of such storms ( Whitaker and Davis 1994 ; Pirret et al
1. Introduction Latent heat release within the atmosphere arises from heat exchanges as water changes phase between vapor, liquid, and solid and is an important component or principal driver for many atmospheric circulations. Even at midlatitudes, latent heating (LH) can be an important part of midlatitude cyclone dynamics and the larger-scale storm track ( Willison et al. 2013 ) and can be especially important for the rapid deepening of such storms ( Whitaker and Davis 1994 ; Pirret et al
. 2012 ; Kidd et al. 2018 ; Houze et al. 2017 ; Duan et al. 2015 ). Over the past decade, significant advances have also been made in numerical weather prediction (NWP) models and global circulation models (GCMs). Yet, accurate prediction of extreme rainfall, quantifying sources of precipitation predictability, and understanding the interactions of large-scale atmosphere–land–ocean dynamics and regional hydroclimate remain important challenges for the research and operational communities. In fact
. 2012 ; Kidd et al. 2018 ; Houze et al. 2017 ; Duan et al. 2015 ). Over the past decade, significant advances have also been made in numerical weather prediction (NWP) models and global circulation models (GCMs). Yet, accurate prediction of extreme rainfall, quantifying sources of precipitation predictability, and understanding the interactions of large-scale atmosphere–land–ocean dynamics and regional hydroclimate remain important challenges for the research and operational communities. In fact
1. Introduction Global precipitation products capitalize upon the long period of record of satellite-based passive microwave (MW) radiometer observations ( Aonashi and Ferraro 2020 ). The passive MW brightness temperature (TB) represents the net top-of-atmosphere upwelling radiation, after taking into consideration the emission and scattering properties of hydrometeors within the top-to-bottom profile, including the contribution from the surface emissivity. The surface precipitation represents
1. Introduction Global precipitation products capitalize upon the long period of record of satellite-based passive microwave (MW) radiometer observations ( Aonashi and Ferraro 2020 ). The passive MW brightness temperature (TB) represents the net top-of-atmosphere upwelling radiation, after taking into consideration the emission and scattering properties of hydrometeors within the top-to-bottom profile, including the contribution from the surface emissivity. The surface precipitation represents
. Climate conditions, topography, and regional land–atmosphere feedbacks drive these aspects of temporal persistence and spatial synchronicity of precipitation, which in turn influence soil moisture, flows, and vegetation. For example, the direction, speed, and size of a storm event moving across a basin can impact downstream flows and ecohydrologic processes. Goodwell and Kumar (2019) explored temporal precipitation persistence and predictability, addressing the extent to which the knowledge of past
. Climate conditions, topography, and regional land–atmosphere feedbacks drive these aspects of temporal persistence and spatial synchronicity of precipitation, which in turn influence soil moisture, flows, and vegetation. For example, the direction, speed, and size of a storm event moving across a basin can impact downstream flows and ecohydrologic processes. Goodwell and Kumar (2019) explored temporal precipitation persistence and predictability, addressing the extent to which the knowledge of past
