Current observation systems that provide data for the analysis and prediction of climate and
day-to-day weather are described, along with plans for future systems. The basic principles …

Observations that are assimilated into numerical weather prediction systems are conformed
by numerous data sets and their impact should be objectively evaluated. This can be …

Abstract 1 This paper is the first publication presenting the predictability of the record-
breaking 2 rainfall in Japan in July 2018 (RJJ18), the severest flood-related disaster since …

Forecast sensitivity to observation (FSO) methods have become increasingly popular over
the past two decades, providing the ability to quantify the impacts of various observing …

In order to conduct observation‐network design experiments for a forecast system, methods
are needed to estimate the benefit of potential observations. Ideally, these methods are …

A particle filter (PF) is an ensemble data assimilation method that does not assume
Gaussian error distributions. Recent studies proposed local PFs (LPFs), which use …

This study conducts a thorough investigation into the behaviors of analysis ensemble
spreads linked to stratospheric sudden warming (SSW) events. A stratosphere-resolving …

An ensemble-based forecast sensitivity to observations (EFSO) diagnosis has been
implemented in an atmospheric general circulation model–ensemble Kalman filter data …

This work assesses the contribution of assimilating AMSU-A satellite-based radiance
measurements to a global data assimilation system based on an atmospheric general …

Adjoints of numerical weather prediction models may be employed for forecast sensitivity to
observations (FSO) in order to monitor the contribution of ingested observation data on short …