All-Sky Satellite Radiance Data Assimilation: Methodology and Challenges - Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications - page 457

19.1 Introduction

Satellites, radars, and other remote sensing are the major sources of information
about atmosphere and oceans with invaluable implications for weather, climate,
and hydrology. Satellites can cover all parts of globe and can provide information
in the areas not accessible by any other observation type. It is not surprising that
satellite radiance observations are widely used in data assimilation and numerical
weather prediction (NWP). Among most relevant data assimilation and NWP
applications are for high-impact weather events such as tropical cyclones and severe
weather outbreaks, which are mostly covered by clouds. Unfortunately, in current
operational practice only clear-sky satellite radiances are commonly assimilated,
with rare exceptions. This effectively filters out potentially useful information from
cloud and precipitation affected radiances and consequently limits the utility of
satellite data. In this paper we will address several challenges related to the use of
all-sky (i.e. combined clear-sky and cloud/precipitation affected) radiances in data
assimilation.
The relevance of all-sky radiance assimilation is widely recognized and discussed
(e.g., Errico et al. 2007a ,b; Auligne et al. 2011 ; Bauer et al. 2011 ). Challenges of
all-sky satellite radiances for data assimilation and prediction can be all traced back
to clouds and precipitation. Cloud microphysical processes are highly nonlinear,
discontinuous, and characterized by very small spatial scales of the order of
hundreds of meters to a kilometer, requiring high-resolution and complex modeling.
Consequently, data assimilation of clouds and precipitation is also nonlinear and
high-resolution. High spatiotemporal resolution of cloud processes has a direct con-
sequence on computations, posing an additional challenge in practical applications.
In this paper we focus on addressing the data assimilation challenges of all-sky
satellite radiance assimilation related to variational and ensemble data assimilation,
since they represent the most relevant methodologies used today. In Sect. 19.2
we present the current status of data assimilation in reference to all-sky radiance
assimilation, and discuss several major challenges in detail in Sect. 19.3 .We
summarize the issues and look at the future of all-sky satellite radiance assimilation
in Sect. 19.4 .

19.2 Current Status

In this section we introduce a more formal overview of data assimilation method-
ologies currently used in research and operations, and also describe current status
of data assimilation with respect to all-sky radiance assimilation.