Extreme Hydroclimatic Events and Multivariate Hazards in a Changing Environment: A Remote Sensing Approach

Extreme Hydroclimatic Events and Multivariate Hazards in a Changing Environment: A Remote Sensing Approach reviews multivariate hazards in a non-stationary environment, covering both short and long-term predictions from earth observations, along with long-term climate dynamics and models. The book provides a detailed overview of remotely sensed observations, current and future satellite missions useful for hydrologic studies and water resources engineering, and a review of hydroclimatic hazards. Given these tools, readers can improve their abilities to monitor, model and predict these extremes with remote sensing.

In addition, the book covers multivariate hazards, like landslides, in case studies that analyze the combination of natural hazards and their impact on the natural and built environment. Finally, it ties hydroclimatic hazards into the Sendai Framework, providing another set of tools for reducing disaster impacts.

• Emphasizes recent and future satellite missions to study, monitor and forecast hydroclimatic hazards
• Provides a complete overview and differentiation of remotely sensed products that are useful for monitoring extreme hydroclimatic and related events
• Covers real-life examples and applications of integrating remote sensing products to study complex multi-hydroclimatic hazards

• Language: English
• Publisher: Elsevier Science
• Release date: Jun 6, 2019
• ISBN: 9780128149003

Book preview

journey.

Part I

Water cycle variables for monitoring hydroclimatic hazards: State-of-the-art and future directions

Outline

Chapter One Quantitative precipitation estimation from satellite observations

Chapter Two Terrestrial water storage

Chapter Three Utility of soil moisture data products for natural disaster applications

Chapter Four Water surface elevation in coastal and inland waters using satellite radar altimetry

Chapter Five Remote sensing techniques for estimating evaporation

Chapter Six Vegetation

Chapter One

Quantitative precipitation estimation from satellite observations

Christopher Kidd¹,² and Vincenzo Levizzani³,    ¹Earth System Science Interdisciplinary Center, University of Maryland, MD, United States,    ²NASA Goddard Space Flight Center, Greenbelt, MD, United States,    ³Institute of Atmospheric Sciences and Climate of the National Research Council (ISAC-CNR), Bologna, Italy

Abstract

The estimation of precipitation (rainfall and snowfall) derived from satellite sensors is now an integral part of monitoring the Earth system. The main advantage of using Earth observation datasets for precipitation estimation is the global perspective that satellites provide. Techniques using these data have exploited a range of satellite systems and their sensors with different, but complementary, frequencies/wavelengths to provide timely precipitation products to the user community. This chapter outlines the fundamentals of satellite precipitation estimation, the satellites and sensors used, the range of techniques and schemes to convert the observations into precipitation products, together with the validation of the precipitation products themselves.

Keywords

Earth observation; precipitation; rainfall; snowfall; extremes

1.1 Introduction

The International Meteorological Vocabulary of the World Meteorological Organization defines precipitation as: Hydrometeor consisting of a fall of an ensemble of particles. The forms of precipitation are: rain, drizzle, snow, snow grains, snow pellets, diamond dust, hail and ice pellets. Precipitation is a key variable in the Earth’s water and energy cycles. As a fundamental element water may take the form of liquid, solid, or vapor, and may exist in all three forms at the same time. It is the transition of water between these different phases that make it so important and difficult to measure. Water vapor is fundamental in the formation of clouds, which are composed of liquid and solid (frozen) water, and from which rainfall and snowfall may precipitate.

The generation of global precipitation products is important for a range of scientific and societal applications (Kirschbaum et al., 2017; Kucera et al., 2013). These include observing and monitoring flash floods, assessing groundwater storage, as well as forecasting crop yields and combating water-borne diseases (Kirschbaum and Patel, 2016). Such applications require spatial scales ranging from local to global and temporal scales from instantaneous to climate (Michaelides et al., 2009). While conventional observations of precipitation from surface-based measurements such as rain gauges and weather radar often form the foundation of precipitation observing systems, their distribution over the Earth’s surface is somewhat limited (Kidd et al., 2017) and availability of data from them is often problematic. Satellite observations of clouds and precipitation have been exploited to provide a range of products that may be used to monitor precipitation occurrence and amounts at a range of spatial and temporal scales.

Perhaps the most important single parameter for precipitation with regard to hydroclimatic hazards is the volume of water over time. The importance of this becomes apparent when dealing with satellite observations, which have specific spatial and temporal sampling characteristics. While Earth observation satellites are capable of providing high-resolution imagery (< 1 m) and imagery as often as every few seconds, the combination of high spatial resolution and high temporal resolution is not possible for any single sensor. For operational quantitative precipitation estimation from satellite sensors, the best spatial resolution is typically in the order of several kilometers with a temporal resolution of 15 minutes or more. However, the temporal and spatial resolution of any observation and subsequent product also has to take into account the directness of the precipitation measurement; the high spatial/temporal resolution products tend to be less directly related to surface precipitation than the poorer spatial/temporal resolution products.

Thus, the relevance of satellite systems for observing precipitation and applications for hazard monitoring has to consider the:

1. resolution (temporal and spatial) of the satellite observations;

2. latency, or availability of observational data and/or products within a certain amount of time;

3. accuracy of the results as determined through validation of data products; and

4. usefulness of the resulting products to user community.

1.2 Satellites and instruments

Since the launch of the first meteorological satellite in 1960, a progression of satellites have been launched that carry sensors capable of providing observations from which surface precipitation may be derived. The majority of these satellite sensors are not necessarily specifically designed for the measurement of precipitation per se. Not until the launch of the Tropical Rainfall Measuring Mission (TRMM; Kummerow et al., 1998; Simpson et al., 1988) in December 1997, later followed by the Global Precipitation Measurement (GPM) mission (Hou et al., 2014) in February 2014, did dedicated satellite precipitation missions exist.

1.2.1 Satellite platforms

Satellites provide an unparalleled view of the Earth and its atmosphere allowing them to observe processes within the Earth system, including those relating to precipitation. The precipitation-capable missions typically comprise of two orbital types: the Low Earth Orbiting (LEO) satellites that circle the Earth at about 850 km altitude or lower, and the Geostationary (GEO) satellites that view the Earth from an altitude of about 36,000 km.

The LEO satellites are often sun-synchronous allowing observations to be made at the same local time and are typical of operational satellites (see Table 1.1), particularly where the overpass time is deemed to be critical. Observations from these satellites are typically available a maximum of twice per day at the Equator, thus limiting the usefulness of any single satellite system for monitoring rapidly changing phenomena such as precipitation, although with multiple satellites more frequent observations may be possible. Satellites such as the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Meteorological Operational satellite (MetOp) series provide stringently maintained orbits, ensuring consistent overpass times. The similar National Oceanic and Atmospheric Administration (NOAA) series of satellites in contrast are less tightly managed and are allowed to drift over time, thus the overpass times will vary slightly; this is in common with other satellite missions such as the Defense Meteorological Satellite Program (DMSP) series (Curtis and Adams, 1987). A number of LEO satellites are placed into nonsun-synchronous orbits that result in overpasses across all the hours of the day, albeit, over an extended period. Such satellites include the TRMM, GPM, and Megha-Tropiques missions; measuring the diurnal variations in precipitation being a key element in their implementation. A consequence of a nonsun-synchronous orbit is that their orbital path will intersect the orbital paths of the sun-synchronous satellites, thus allowing the intercomparison and/or cross-calibration of instantaneous satellite observations from different satellite sensors.

Table 1.1

GEO satellites remain (nearly) stationary with respect to their subsatellite position on the Earth’s surface. From their orbital location frequent and regular images can be acquired over a full disc of the Earth, although to obtain (quasi-) global coverage a constellation of satellites located around the Equator is required. The main geostationary satellites currently providing this global coverage include the US NOAA Geostationary Operational Environmental Satellite (GOES)-15/16 (Goodman et al., 2012; Schmit et al., 2017), the European Meteosat Second Generation (MSG) Meteosat-8/9/10 (Schmetz et al., 2002), and the Japanese Himawari (Bessho et al., 2016), with additional geostationary satellites provided by the China Meteorological Agency (CMA) Feng-Yun (FY)-series and the Indian National Satellite System (INSAT)-3 series (see Table 1.2).

Table 1.2

aCurrently undergoing commissioning.

Source: WMO OSCAR database.

1.2.2 Sensors

Satellite platforms host one or more instruments that provide the sensing capabilities. The development of sensors for observing precipitation has largely concentrated upon visible (VIS), infrared (IR), and microwave (MW) systems, the latter covering both passive microwave (PMW) radiometers and active microwave (AMW, or radar) instruments. At present the geostationary platforms only carry VIS/IR instruments, while the LEO platforms may carry one or more VIS/IR, PMW or AMW sensors.

Development of satellite-based precipitation measurements were first based upon the VIS/IR observations; the identification of clouds being fundamental in observing and monitoring precipitation, or at least precipitation-related systems. However, VIS/IR observations are indirectly related to surface precipitation since they only relate to information obtained from the cloud top properties. Nevertheless, such techniques are commonly used due to the relative ease of accessing the data and subsequent analysis together with the frequency and resolution of the imagery acquired, particular when obtained from geostationary satellite sensors.

More direct observations of precipitation are possible through PMW sensors that sense the upwelling radiation from the Earth’s surface. Over radiometrically cold surfaces (such as water), precipitation enhances the signal, while over radiometrically warm surfaces (e.g., land) precipitation can scatter the upwelling radiation, resulting in a decrease in the received signal. Although more direct than the VIS/IR observations, PMW observations are only available from LEO satellites, and thus provide only intermittent samples. In addition, since the level of radiation emanating from the Earth and the atmosphere in the MW region is small, the spatial resolution of the observations is much poorer than that of VIS/IR sensors.

PMW sensors include both imagers (those operating at frequencies within atmospheric window channels) and sounders (those that operate at, or close to, atmospheric absorption bands), with many newer instruments encompassing both imaging and sounding channels. Conically-scanning instruments (typically imagers) are usually preferred for precipitation retrievals due to consistent Earth incidence angle (EIA), polarization, and resolution. Cross-track instruments (typically sounders) scan perpendicular to the satellite’s track and consequently have a variable EIA that affects the spatial resolution and polarization of the observations; however, since their observations are typically close to atmospheric absorption bands they are less sensitive to the surface background. Tables 1.3 and 1.4 summarize the PMW satellites and sensors since 1978.

Table 1.3

Table 1.4

The most direct satellite-based observations of precipitation come from AMW measurements. The basis of such measurements is similar to surface-based radar systems, converting backscattered radiation to a precipitation measurement. However, the small number of available sensors and limited swath width results in poor temporal sampling, although the longevity of the TRMM mission (Kummerow et al., 1998, 2000; Simpson et al., 1988) with its Precipitation Radar (PR; Kozu et al., 2001), and the current GPM mission (Hou et al., 2014) with the Dual-frequency Precipitation Radar (DPR; Kojima et al., 2012) now provide a long-term record of precipitation across the Tropics. In addition, CloudSat (Stephens et al., 2002) provides valuable information, particularly at the higher latitudes, on light rainfall and snowfall due to the sensitivity of the Cloud Profiling Radar (CPR).

1.2.3 Current precipitation observing systems

To maximize the availability of precipitation data, a range of different satellite systems are used to provide observations. These can be split broadly into the GEO IR-based observing network and PMW/AMW LEO satellites that form the GPM constellation. The GEO suite of sensors is maintained to provide a consistent set of observations around the Equator and extending from about 60°N to 60°S. Although individual satellites are capable of providing higher temporal and spatial resolution, a combined IR brightness temperature (Tb) product is available every 30 minutes at a nominal resolution of 4 km (Janowiak et al.,