Hydrometeorology E-Book

Christopher G. Collier

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Serie: Advancing Weather and Climate Science
• Sprache: Englisch

Seitenzahl: 682

Veröffentlichungsjahr: 2016

Beschreibung

Hydrometeorology presents an introduction to relevant topics in the interdisciplinary fields of hydrology and meteorology. This book is one of the few books aiming to provide a balance between aspects of meteorological and hydrological processes. The transfer of energy and water between the land surface and lower atmosphere within the hydrological cycle is addressed followed by a description of the nature of precipitation, and how it is formed. Forecasting precipitation is reviewed on all scales, and the range of rainfall-runoff models and coastal surge models and forecasts (including tsunamis) which have been, and are being, used are discussed.

The mechanisms of snow, ice (glacier, sea and tundra), evaporation and transpiration, how drought occurs and the representation of wind are described. How rainfall (including radar measurements) and river flow information is gathered and analysed (including, frequency analysis, Probable Maximum Precipitation and Flood) are presented. Satellite measurements of precipitation are discussed. Examples of major past floods and droughts are given.

Past and future climate change, which is included, underpins the importance of hydro-meteorological processes. The structure of the general circulation of the atmosphere and how it influences weather and climate including the Hadley, Ferrel and Polar cells, the Trade winds and the El Nino, is outlined. Finally, the influence of urban areas on rainfall formation, dealing with urban drainage and air quality are described.

Each chapter ends with one or two specific points as appendices, elements discussed in the chapter and a list of sample problems to aid understanding.

Readership: This book is aimed at 3rd year undergraduate and postgraduate students on hydrology/hydrometeorology, environmental science and geography courses. Professionals in environmental protection agencies and consultancies will also find the book of great interest. It contains a balance of both the physics and mathematics which underpin such courses and activities.

Leseprobe

Table of Contents

Cover

Title Page

Series Foreword

Preface

Acknowledgements

About the Companion Website

1 The Hydrological Cycle

1.1 Overview

1.2 Processes comprising the hydrological cycle

1.3 Global influences on the hydrological cycle

1.4 Water balance

1.5 Impact of aerosols on the hydrological cycle

1.6 Coupled models for the hydrological cycle

1.7 Global Energy and Water Cycle Exchanges Project (GEWEX)

1.8 Flooding

References

2 Precipitation

2.1 Introduction

2.2 Equation of state for a perfect gas

2.3 Hydrostatic pressure law

2.4 First law of thermodynamics

2.5 Atmospheric processes: dry adiabatic lapse rate

2.6 Water vapour in the atmosphere

2.7 Atmospheric processes: saturated adiabatic lapse rate

2.8 Stability and convection in the atmosphere

2.9 The growth of precipitation particles

2.10 Precipitation systems

2.11 Global atmospheric circulation

Appendix 2.1 Growth of a raindrop 2.1

References

3 Evaporation and Transpiration

3.1 Introduction

3.2 Modelling potential evaporation based upon observations

3.3 Aerodynamic approach

3.4 Energy balance

3.5 The Penman equation

3.6 Sensible and water vapour fluxes

3.7 Evaporation of water from wet vegetation surfaces: the interception process

3.8 Measuring evaporation and transpiration

3.9 Water circulation in the soil–plant–atmosphere continuum

3.10 Water circulation and transpiration

3.11 Water flux in plants

3.12 Modelling land surface temperatures and fluxes

3.13 Soil–vegetation–atmosphere transfer schemes

3.14 Estimation of large scale evapotranspiration and total water storage in a river basin

Appendix 3.1 Combination of aerodynamic and energy balance methods of computing lake evaporation

Appendix 3.2 Modelling soil moisture wetness

References

4 Snow and Ice

4.1 Introduction

4.2 Basic processes

4.3 Characteristics of snow cover

4.4 Glaciers

4.5 Sea ice

4.6 Permafrost

4.7 The physics of melting and water movement through snow

4.8 Water equivalent of snow

4.9 Modelling snowmelt and stream flow

4.10 Snow avalanches

4.11 Worldwide distribution and extremes of snow cover

Appendix 4.1 Estimates of catchment snowmelt inflow rates

References

5 Measurements and Instrumentation

5.1 Measurement, resolution, precision and accuracy

5.2 Point measurements of precipitation

5.3 Areal measurements of precipitation using raingauge networks

5.4 Radar measurements of rainfall

5.5 Soil moisture

5.6 Evaporation and evapotranspiration

5.7 Flow measurement: basic hydrometry

5.8 Measuring stream discharge

5.9 Brief overview of modern telemetry

Appendix 5.1 Combining dissimilar estimates by the method of least squares

References

6 Satellite-Based Remote Sensing

6.1 Overview of satellite remote sensing

6.2 Surface scattering of electromagnetic radiation

6.3 Interaction of electromagnetic radiation with the atmosphere

6.4 Visible and infrared data

6.5 Multispectral data

6.6 Passive microwave techniques

6.7 Active (radar) microwave techniques

6.8 The surface energy balance system (SEBS)

6.9 Summary of satellite measurement issues

Appendix 6.1 Radiation balance

References

7 Analysis of Precipitation Fields and Flood Frequency

7.1 Introduction

7.2 Areal mean precipitation

7.3 Spatial and temporal storm analysis

7.4 Model storms for design

7.5 Approaches to estimating flood frequency

7.6 Probable maximum precipitation (PMP)

7.7 Probable maximum flood (PMF)

7.8 Flood Studies Report (

FSR

)

7.9

Flood Estimation Handbook

(

FEH

)

Appendix 7.1 Three-dimensional description of a rainfall surface

Appendix 7.2 Gumbel distribution

References

8 Precipitation Forecasting

8.1 Introduction

8.2 Nowcasting

8.3 Probabilistic radar nowcasting

8.4 Numerical models: structure, data requirements, data assimilation

8.5 Medium range forecasting

8.6 Seasonal forecasting

Appendix 8.1 Brier skill score

References

9 Flow Forecasting

9.1 Basic flood forecasting techniques

9.2 Model calibration and equifinality

9.3 Flood forecasting model development

9.4 Conversion of detailed hydrodynamic models to simplified models suitable for real-time flood forecasting

9.5 Probabilistic flood forecasting and decision support methods

9.6 Derivation of station rating (stage-discharge) curves

9.7 Performance testing of forecasting models and updating procedures

9.8 Configuration of models on to national and international forecasting platforms

9.9 Flood warnings and levels of service

9.10 Case studies worldwide: river and urban

Appendix 9.1 St Venant equations

Appendix 9.2 Flow in unsaturated and saturated zones

References

10 Coastal Flood Forecasting

10.1 Types of coastal flooding

10.2 Models used to predict storm surge flooding

10.3 Probabilistic surge forecasting

10.4 Tsunamis

10.5 Examples of coastal flooding in the United Kingdom

10.6 Some examples of coastal flooding worldwide

Appendix 10.1 Wave overtopping at the coast

References

11 Drought

11.1 Definitions

11.2 Drought indices

11.3 The physics of drought

11.4 Frequency analysis: predictability

11.5 Modelling the occurrence of drought

11.6 Major drought worldwide

11.7 Examples of the consequences of drought

11.8 Strategies for drought protection, mitigation or relief

Appendix 11.1 Defining aridity

References

12 Wind and the Global Circulation

12.1 Equations of motion

12.2 Atmospheric Ekman layer

12.3 Fronts

12.4 Jet streams

12.5 Hurricanes

12.6 Lee waves

12.7 Land and sea breezes

12.8 The wind structure of the atmospheric circulation

12.9 Hadley cell

12.10 Polar cell

12.11 Ferrel cell

12.12 Walker circulation

12.13 El Niño/Southern Oscillation

12.14 Monsoons

Appendix 12.1 Large scale air motion

Appendix 12.2 Ageostrophic motion

References

13 Climatic Variations and the Hydrological Cycle

13.1 An introduction to climate

13.2 Evidence of climate change

13.3 Causes of climatic change

13.4 Modelling climatic change

13.5 Possible effects of climate change upon the hydrological cycle and water resources

Appendix 13.1 Estimating return times for events in a long term climate record

References

14 Hydrometeorology in the Urban Environment

14.1 Introduction

14.2 Urban boundary layer and the water cycle

14.3 Urban development and rainfall

14.4 Sewer flooding

14.5 Surface runoff from urban areas

14.6 Floodplain development

14.7 Acid rain

14.8 Urban air and water pollution

Appendix 14.1 Number of runoff events from an urban drainage system

References

Glossary

Index

End User License Agreement

List of Tables

Chapter 01

Table 1.1 Water in the hydrosphere and the distribution of fresh water on the Earth (from Martinec, 1985)

Table 1.2 Average residence times for specific stores (see for example www.physicalgeography.net/fundamentals/8b.html)

Chapter 02

Table 2.1 Atmospheric scale classification

Table 2.2 Scales of precipitation systems (partly after Browning, 1983a)

Table 2.3 Examples of rainfall totals from intense thunderstorms occurring worldwide

Table 2.4 Examples of extreme tropical storm rainfall totals occurring worldwide

Chapter 03

Table 3.1 MORECS albedos (from Thompson et al., 1981)

Chapter 04

Table 4.1 Percentage of incident short wave radiation reflected by some surfaces

Table 4.2 Densities of snow cover (from Gray and Male, 1981)

Table 4.3 Snowfall accumulations (cm) in specified durations for a frequency of occurrence per year and specified return periods at Birmingham (Elmdon) and (in brackets) Eskdalemuir (Dumfries and Galloway) (from Jackson, 1977b)

Chapter 05

Table 5.1 Main components of the systematic error in precipitation measurements and their meteorological and instrumental factors, listed in order of general importance (after WMO, 1982)

Table 5.2 Typical relationships between

Z

and

R

Table 5.3 Example values of equivalent radar reflectivity factor

Z

e

(dBZ) for rain and snow for two precipitation rates (from Smith, 1984)

Chapter 06

Table 6.1 Satellite systems used for hydrometeorological studies

Table 6.2 Typical values of albedo (from Schanda, 1986; Rees, 1993)

Table 6.3 TRMM precipitation-related instruments (after Liu et al., 2012)

Table 6.4 Summary of the performance of satellite rainfall estimation techniques

Table 6.5 Examples of values of equilibrium temperature and mean surface temperature for selected planets (Harries, 1994)

Chapter 07

Table 7.1 Flood frequency terminology

Chapter 08

Table 8.1 Examples of typical linear extrapolation timescales for precipitation fields associated with various weather events (from Collier, 1996, partly from Doswell, 1986)

Chapter 09

Table 9.1 The meaning of the Environment Agency flood warnings

Chapter 11

Table 11.1 Summary of the commonly used drought indices (from Mu et al., 2013)

Chapter 13

Table 13.1 Characteristics of paleoclimatic data sources (after Mason, 1976)

Table 13.2 Global average (a)–(e) January values and (f) August values for four climate simulations: Ice Age I (18,000 years before present); Ice Age II (as Ice Age I with sea surface temperature reduced by 2 °C); Double CO

2

(carbon dioxide); Mesozoic (65 million years before present) (from Rind, 1986)

List of Illustrations

Chapter 01

Figure 1.1 Simplified representation of the hydrological cycle

Figure 1.2 Meridional distribution of zonal mean precipitable water (mm): (a) over land and sea, (b) mean over land only, and (c) mean over sea only. Annual mean, December-January-February (DJF) mean, and June-July-August (JJA) mean, for 4 years from 1989 to 1992

Figure 1.3 Illustrating (a) terrestrial water balance, (b) atmospheric water balance and (c) combined atmospheric–terrestrial water balance

Chapter 02

Figure 2.1 Pressure–volume graph for water known as an Amagat–Andrews diagram. Shows phase changes along isotherms in the (

p

,

V

) domain.  A sample of water vapour is considered at a state corresponding to point A, i.e. at a temperature

T

1

and pressure

p

1

greater than the triple point temperature

T

t

and pressure

p

t

. If the vapour is compressed isothermally, the pressure increases until point A

1

is reached when liquid water and water vapour coexist in equilibrium, i.e. some water vapour has condensed to form liquid water

Figure 2.2 Sloping convection: an N–S cross-section with isentropic surfaces (surfaces of constant potential temperature θ) indicated, comparing the potential energy released when a parcel of air moves vertically, horizontally or intermediately

Figure 2.3 Illustrating the growth of ice spheres and decay of water drops in a mixture subject to a constant updraught of 1 m s

– 1

. The air is assumed to be initially saturated with respect to water. The dashed line shows the growth of the droplets in the absence of any ice particles

Figure 2.4 The evolution of warm and cold rain starting from cloud condensation nuclei (CCN) and ice nuclei (IN)

Figure 2.5 Illustrating (a) reflectivity

Z

(using horizontal polarization of the radar beam, see Chapter 5) and (b) differential reflectivity

Z

DR

(the ratio of horizontal and vertical polarizations of the radar beam, see Chapter 5) reconstructed from measurements made at constant elevation angles by the NCAS mobile X-band dual polarization Doppler radar on 3 August 2013 at 1327 UTC

Figure 2.6 (a) Schematic model of a multi-cell hailstorm observed near Raymer, Colorado. It shows a vertical section along the storm’s north to south (N–S) direction of travel, through a series of evolving cells. The solid lines are streamlines relative to the moving system. The hail cascade represents the trajectory of a hailstone during its growth from a small particle at cloud base. Lightly stippled shading represents the extent of cloud, and the three darker grades of stippled shading represent radar reflectivities of 35, 45 and 50 dBZ. Environmental winds (m s

–1

, degrees from north) relative to the storm are shown on the right-hand side of the figure (from Browning et al., 1976). (b) Vertical section corresponding to (a). The radar echo distribution and cloud boundaries are as before. Trajectories 1, 2 and 3 represent the three stages in the growth of large hailstones. The transition from stage 2 to stage 3 corresponds to the re-entry of a hailstone embryo into the main updraught prior to a final up-and-down trajectory during which the hailstone may grow to a large size, especially if it grows close to the boundary of the vault as in the case of the indicated trajectory 3. Other, less favoured hailstones will grow a little farther from the edge of the vault, and will follow the dotted trajectory. Cloud particles growing within the updraught core are carried rapidly up and out into the anvil along trajectory 0 before they can attain precipitation size

Figure 2.7 Schematic of a convective outflow in vertical cross-section: PM is the surface pressure reaching a local minimum; PJ is the increase or jump due to a dynamic deceleration between the cold and warm air masses;  WS is the beginning of the wind shift as the cold air arrives;  TD is the temperature break or drop as the cold air passes through; H is the head; and NH is the nose head (from Droegemeier and Wilhelmson, 1987; Trapp, 2013)

Figure 2.8 Model depicting the main features of the large scale flow that determine the distribution of cloud and precipitation in a mid-latitude depression. The arrows represent flow, the height of which is labelled in millibars. The scalloped line represents the outline of the cloud pattern, and the dashed shading represents the extent of the surface precipitation. SCF is surface cold front, SWF is surface warm front

Figure 2.9 Schematic integrated water vapour values covering the lifetime of a depression based upon microwave radiometer data; units are kg m

– 2

Figure 2.10 Major types of rain bands (stippled) observed in mid-latitude depressions: type 1, warm front bands; type 2, warm sector bands; type 3, cold front bands; type 4, upper level cold surge bands (situated along the leading edge of cold air overrunning the warm front); type 5, line convection (a narrow band or series of line elements along the cold front)

Figure 2.11 Hurricane Katrina over the Gulf of Mexico at its peak, 28 August 2005; category 5, highest winds 175 mph (280 km h

– 1

), lowest pressure 902 mbar (hPa)

Figure 2.12 Mechanisms of orographic rain generation (see text)

Figure 2.13 Distribution of mean rainfall intensity (mm h

– 1

) within a vertical section (AB) along the direction of motion of rain areas travelling from the sea over the hills of South Wales, UK, during a 5 hour period of warm sector rain. The inset shows the orientation of the section AB in relation to the coastline and hills (greater than 400 m altitude)

Figure 2.14 Globally averaged annual precipitation 1980–2004 Jan–Dec (mm per month) from the Global Precipitation Climatology Project (GPCP) Version 2

Figure 2.15 Satellite image in the visible wavelengths taken from visible data gathered by the European geostationary satellite MSG at 1200Z on 5 October 2012. Note the cloud associated with the ITCZ north of the equator. The cloud-free Sahara desert is clearly visible, as are cloud clusters in the tropics and mid-latitude depressions (courtesy of Eumetsat)

Chapter 03

Figure 3.1 Relationship between saturated vapour pressure (or saturated specific humidity) and temperature, illustrating what is referred to as the

del approximation

(see section 3.5) (from Calder, 1990)

Figure 3.2 Schematic diagram illustrating how the latent heat flux

λE

is driven by humidity gradients between the inside of the stomatal cavity

e

s

(

T

0

) and the leaf surface

e

0

and the bulk atmosphere

e

against the stomatal and aerodynamic transfer resistances (from Calder, 1990)

Figure 3.3 (a) Comparison of soil moisture content as measured by a capacitance probe (fainter line), lysimeter (darker line) and SAR (circles). (b) Retrieved cumulative evapotranspiration totals from a capacitance probe (fainter line) and a lysimeter (darker line) (from Fox et al., 2000)

Figure 3.4 Schematic representation of the variation of water potential in different sectors of the SPAC: (1) moist soil, low evaporation rate; (2) moist soil, high evaporation rate; (3) dry soil, low evaporation rate; (4) dry soil, high evaporation rate (from Cruiziat, 1991; Guyot, 1998)

Figure 3.5 (a) Schematic representation of a plant in ohmic form for a conservative flux (from Cruiziat and Tyree, 1990; Guyot, 1998); (b) schematic representation of a plant in ohmic form for a non-conservative flux (from Guyot, 1998)

Figure 3.6 Illustrating the phase difference between transpiration and absorption in plants (from Guyot, 1998)

Figure 3.7 Flow chart for MOSES and MORECS. All boxes are part of MOSES; those with a dashed border show the structure of MORECS. The arrows show the flows of water.

T

1

etc. are the mean temperatures of the four soil layers in MOSES, and

T

* is a ‘skin’ surface temperature which is calculated for each MOSES land use.

R

s

is the canopy resistance to moisture flow, which has fixed monthly values in MORECS but is interactive in MOSES.

R

a

is the resistance to vapour flow from the canopy to the level where temperature and humidity are measured. The box labelled ‘phase change’ refers to the physical processes when ice changes to water and back again. The box showing ‘Darcian flow’ refers to flow for which the specific discharge is related to the hydraulic gradient (from Hough, 2003)

Figure 3.8 Schematic diagram of early SVATs (after Budyko, 1956 from Shuttleworth, 2012)

Figure 3.9 Schematic diagram of SVATs with improved representation of hydrologic processes:

S

r

is canopy capacity (saturation of canopy),

H

is sensible heat,

L

is latent heat,

P

is precipitation,

S

is incoming solar radiation,

μ

is fraction of precipitation in each grid square (from Shuttleworth, 2012)

Chapter 04

Figure 4.1 Flow diagram of the formation of different types of snow

Figure 4.2 Snowflake structures

Figure 4.3 Rates of precipitation from adiabatically ascending air for a 100 m layer with a vertical velocity of 1 m s

– 1

Figure 4.4 Patterns of latitudinal seasonal snow cover

Figure 4.5 Ground temperature profile in a permafrost region;

T

1

and

T

2

represent different mean surface temperature conditions

Figure 4.6 Temporal albedo variations of a melting snow cover

Figure 4.7 Nomogram for the assessment of snowfall density

ρ

. Average wind speed

u

at the 2 m level on days with snowfall: (a) exposed locations,

; (b) open locations,

; (c) sheltered locations,

; (d) completely sheltered locations,

Figure 4.8 Five-year return water equivalent of lying snow (mm), reduced to sea level

Figure 4.9 Flow chart of a computer simulation model

Figure 4.10 Satellite-derived snow cover estimates versus measured runoff for (a) the Indus River above Besham, Pakistan, 1974–9; and (b) the Kabul River above Nowshera, Pakistan, 1974–9. Regression values for the lines are shown for each graph, where

y

is runoff,

S

is snow cover and

r

is the correlation coefficient

Figure 4.11 Rain and melt close to the surface form water in the snow cover; when water accumulates at a boundary between layers the strength of the snow is reduced and avalanches can occur

Figure 4.12 World distribution of snow cover, February 2000:

grey

areas, less than 20% of the land area covered;  

white areas

, 100%

Figure 4.13 Arctic sea ice extent for 17 September 2014; the grey line shows the 1981 to 2010 median extent for that day; the black cross indicates the geographic North Pole

Figure 4.14 Temperature–snowmelt relationship for different values of initial water equivalent for a lowland catchment

Chapter 05

Figure 5.1 Precision and accuracy: (a) accurate and precise, (b) not accurate but precise, (c) accurate but not precise, (d) not accurate and not precise

Figure 5.2 The Joss–Waldvogel disdrometer at the Karlsruhe Institute of Technology; the measurement surface has an area of 48 cm

2

Figure 5.3 The Folland-shaped gauge with the door open showing the collecting bottle

Figure 5.4 The percentage difference in catch between the Folland-shaped gauge (FSG) and the 5 inch gauge for increasing wind speed

Figure 5.5 (a) The geometry of the radar beam relative to the curvature of the Earth. A radar pulse having a length

l

is located at a range

r

from the radar. The height of the base of the beam at range

r

having an angular width of

θ

is

h

. (b) Permanent echoes (PE) and screening caused by hills close to the radar site are also shown

Figure 5.6 Reflectivity (dBZ) measured by the NCAS mobile radar at a constant elevation angle of 2.5° on 3 August 2013 during the COnvective Precipitation Experiment (COPE)

Figure 5.7 Absolute error (%) in 5 minute accumulations as a function of the resolution of the reflectivity maps and sampling intervals

Figure 5.8 Vertical profiles seen by radar at various ranges in (a) convective rain, (b) widespread rain, (c) low level rain or snow, and (d) orographic (very low level) rain. The numbers in each figure give the percentage (referred to the true melted water value, which would be measured at ground level using a raingauge) of rain rate deduced from the maximum reflectivity of the profile. A radar with a 1° beam width is assumed in a flat country. If the radar is lower than nearby obstacles, then much less precipitation can be observed at far ranges. The top and bottom of the main part of a 1° beam elevated at 0.5° are shown as dashed lines labelled 0° and 1°

Figure 5.9 Mean error of the hourly rainfall totals in river catchments of average area 60 km

2

as determined from radar measurements in various kinds of rainfall conditions, plotted as a function of the number density of adjusting raingauge sites (solid lines). Also shown for comparison is the mean error of the hourly subcatchment totals as determined from a network of raingauges in the absence of radar, again plotted as a function of the number density of raingauge sites (dotted lines).  The set of four dotted curves represents the measurement errors for the raingauge network in the presence of (1) extremely isolated showers, (2) typical showers, (3) typical widespread rain and (4) extremely uniform rain. For all curves the mean error is defined as the mean value of the difference between the estimated rainfall and the ‘optimum estimate’ without regard to sign

Figure 5.10 Schematic representation of the problems associated with the measurement of precipitation by radar: (1) radar beam overshooting the shallow precipitation at long ranges; (2) low level evaporation beneath the radar beam; (3) orographic enhancement above hills which goes undetected; (4) the bright band; (5) underestimation of the intensity of drizzle because of the absence of large droplets; (6) radar beam bent in the presence of a strong hydrolapse, causing it to intercept land or sea

Figure 5.11 (a) Reflectivity and (b) differential reflectivity

Z

DR

reconstructed from measurements made at constant elevation angles by the NCAS mobile X-band dual-polarization Doppler radar on 3 August 2013 at 132740 UTC

Figure 5.12 The dependence of the mean percentage error, regardless of sign, of estimates of snow depth over areas of 100 km

2

derived from radar data, on the assumed height of the melting level

Figure 5.13 Vertical section of the supercell storm of 21 July 1998 at 1741 UTC along 232° azimuth from the POLDIRAD radar, DLR, Germany. ITF flashes are plotted for a 30 s interval around the nominal scanning time. Hydrometeor or particle colour codes: SR, small rain; LR, large rain; S, snow; G, graupel; RH, rain–hail mixture; H, hail; HW, hail wet; HLWS, hail large wet spongy; HLW, hail large wet; RLH, rain/large-hail mixture)

Figure 5.14 COSMOS station (courtesy CEH)

Figure 5.15 Diagram to show the principle and theory of the weir equation of discharge: the parameters relate to equations 5.21 and 5.22

Figure 5.16 Schematic view of measuring cross-section. The cross-section is divided into segments by spacing verticals at a sufficient number of locations across the channel.  The discharge is derived from the sum of the products of velocity, depth and distance between the verticals

Figure 5.17 The stage–area–velocity method for extrapolating a stage-discharge curve

Figure 5.18 The path taken from an outstation, via METEOSAT, through its ground station and back to the user through the retransmission WEFAX route and over the WMO GTS network

Chapter 06

Figure 6.1 Electromagnetic spectrum and satellite instrumentation associated with specific wavelength intervals (after Hall and Martinec, 1985)

Figure 6.2 Radiation, initially of flux density

F

, is incident at angle

θ

0

on an area d

A

and is then scattered into solid angle d

Ω

1

in a direction

θ

1

. The azimuthal angles

ϕ

0

and

ϕ

1

are omitted for clarity (from Rees, 1993)

Figure 6.3 Typical spectral albedos of various materials in the visible and near infrared (from Rees, 1993)

Figure 6.4 Microwave emissivities

ε

in the normal direction of various materials at a range of frequencies

ν

(from Rees, 1993)

Figure 6.5 Total zenith attenuation by the atmosphere under normal conditions (simplified) (from Rees, 1993)

Figure 6.6 Observed surface rainfall 90 minute totals

R

and cloud top temperatures CTT over south-east Australia for cumuliform cloud or cloud in the convective sector of extratropical cyclones; the points are derived from several studies

Figure 6.7 Rainfall estimates from infrared satellite data, 1630 GMT 8 October 2012: the US satellite images displayed are infrared (IR) images. Warmest (lowest) clouds are shown in white; coldest (highest) clouds are displayed in shades of yellow, red and purple. Imagery is obtained from the GOES and METEOSAT geostationary satellites, and the two US Polar Orbiter (POES) satellites. POES satellites orbit the Earth 14 times each day at an altitude of approximately 520 miles (870 km)

Figure 6.8 Illustrating (a) a classification in a three-dimensional intensity space of cloud, fog, land and water; (b) cloud analysed using this classification at 1500 UTC 24 May 1975 over southern Scandinavia; and (c) the weather observed about 1.5 hours after the satellite passage (after Liljas, 1982)

Figure 6.9 Typical reflectance curve for snow (O’Brien and Munis, 1975) showing saturation levels for visible and near infrared bands of the thematic mapper (TM) and multispectral scanner (MSS)

Figure 6.10 Bipolarization (horizontal/vertical) plot of rainfall rates with the observed relationship between radar rainfall rates and SMMR brightness temperature

T

B

during the summer over the United States (after Spencer, 1986)

Figure 6.11 Global Precipitation Mission (GPM) Constellation. Suomi NPP, National Polar-orbiting Partnership (2011–); JPSS-1, NOAA Joint Polar Satellite System (2017–); GCOM-W1, Global Change Observation Mission (2012–); Megha-Tropiques, French Water Cycle and Energy Budget in the Tropics (2011–) (see also Table 6.1) (from pmm.nasa.gov/GPM)

Figure 6.12 Brightness temperature versus snow depth measured at (a)

, horizontal polarization, by the NIMBUS-5 ESMR, and (b)

, vertical polarization, by the NIMBUS-6 ESMR (after Rango et al., 1979 from Ulaby et al., 1986)

Figure 6.13 Arctic (top panels) and Antarctic (bottom panels) sea ice concentration climatologies from 1978 to 2002: approximate seasonal winter maximum (February in the Arctic and September in the Antarctic) and minimum (September in the Arctic and February in the Antarctic) levels (image provided by National Snow and Ice Data Center, University of Colorado, Boulder, CO)

Figure 6.14 Geometry of SEASAT SAR

Figure 6.15 Comparison of soil moisture content as measured by a capacitance probe (fainter line), lysimeter (darker line) and ERS-1 SAR (circles); spikes show instrumental noise

Figure 6.16 (a) TRMM monthly mean rainfall (mm) January and February 1998 and (b) the difference in two-month mean rainfall between 1998 and 1999 (GSFC, NASA)

Figure 6.17 The interactions of high (e.g. 85 GHz) and low (e.g. 19 GHz) frequency passive microwave with precipitation clouds and the surface. The width of the vertical columns represents the intensity or temperature of the upwelling radiation. In this figure the illustrated features and their demarcations are: (a) the small emissivity of sea surface for both low (1) and high (2) frequencies; (b) the large emissivity of land surface for both low (3) and high (4) frequencies; (c) the emission from cloud and raindrops, which increases with vertically integrated liquid water for the low frequency (5), but saturates quickly for the high frequency (6); (d) the signal of the water emissivity at the low frequency is masked by the land surface emissivity (7); (e) the saturated high frequency emission from the rain (8) is not distinctly different from the land surface background (4); (f) ice precipitation particles aloft backscatter down the high frequency emission (9), causing cold brightness temperatures (10), regardless of surface emission properties; (g) the ice lets the low frequency emission upwell unimpeded (11), allowing its detection above cloud top as warm brightness temperature (12) (from Rosenfeld and Collier, 1999)

Chapter 07

Figure 7.1 Isohyetal method of estimating areal precipitation (from Shaw, 1994)

Figure 7.2 Curves showing the typical relationship between maximum storm depth, area covered and duration in hours (from Shaw, 1994)

Figure 7.3 Example of the calculation of area-average precipitation using the Thiessen method (from Sumner, 1988 and Shuttleworth, 2012)

Figure 7.4 Schematic diagram of the hypothetical variation in correlation coefficient versus distance for long term average precipitation relative to one location if produced by randomly occurring convective storms over a moist, flat, featureless plain (from Shuttleworth, 2012)

Figure 7.5 Double mass analysis for the accumulated rainfall in millimetres for several raingauge sites, confirming that there is a problem at the Botanic Gardens gauge

Figure 7.6 Mean relative error (%) as a function of the selected number of stations per grid box in Australia for February and in Germany and the United States for August 1987 (from Rudolf et al., 1984)

Figure 7.7 Design profiles for storms with 90 and 75 percentile points of profile peakedness (summer and winter) (

Flood Studies Report

, vol. 1, NERC, 1975)

Figure 7.8 Fisher–Tippett distributions types I, II and III

Figure 7.9 Areal reduction factors related to rain area and duration (from Shuttleworth, 2012, after Sumner, 1988 and Rodda et al., 1976)

Figure 7.10 Single site flood frequency curve for the River Thames at Eynsham, fitted by the method of L-moments (a robust way of summarizing a distribution: see for example Hosking and Wallis, 1997) using a generalized logistic (GL) distribution; the broken line is the upper bound of the fitted distribution (from Institute of Hydrology, 1999)

Figure 7.11 Rainfall growth curves, which provide a multiplier of the index rainfall. Designs are commonly based upon rainfall events with a frequency of between once in 2 years and once in 100 years, denoted by a return period of M2 for once in 2 years, M100 for once in 100 years etc. The curves show the growth curves for particular rainfall amounts as follows: for England and Wales: (a) 2 hour rainfall, (b) 1 day rainfall for M5 30–40 mm, (c) 2 day rainfall for M5 40–50 mm, (d) 1 day rainfall for M5 60–75 mm, (e) 4 day rainfall for M5 75–100 mm, (f) 8 day rainfall for M5 100–150 mm, (g) 25 day rainfall for M5 150–200 mm, (h) 8 day rainfall for M5 200–300 mm (NERC, 1975)

Figure 7.12 Flow chart summary of

FEH

rainfall frequency analysis (Institute of Hydrology, 1999)

Figure 7.13 Flow chart summary of

FSR

rainfall frequency analysis (NERC, 1975)

Figure 7.14 Depth–duration–frequency model fitted to design rainfalls for Waddington (Institute of Hydrology, 1999)

Chapter 08

Figure 8.1 The quality of weather forecasts, defined as the product of the accuracy and detail achievable, shown as a function of lead time for three different forecasting methods. The figure is highly schematic, and the stage at which the quality of one technique becomes superior to another will change

Figure 8.2 Rainfall observed by the UK radar network at 1400 UTC on 15 April 1986. Meteorological stations providing conventional observations are shown (•).  The locations of AWS observations are also indicated (+) (1985). Note that the full extent of the rain band is not observed by the conventional observations

Figure 8.3 Positions of low between 1800 and 2400 UTC on 22 December 1983 according to the analyses of the Central Forecasting Office at the Met Office, Bracknell, UK. Each position is defined by the innermost two isobars (2 hPa intervals) irrespective of the actual pressure values. The possible track inferred from analyses between 1800 and 2000 is shown by the broken arrow, whilst the direction of movement suggested by radar data up to 2130 is shown by the bold full arrow. The 2130 radar picture (available within 2 min) was available before the 2100 surface chart

Figure 8.4 (a) The mean error regardless of sign in the forecast hourly rainfall for the 20 km square (400 km

2

) centred on Malvern plotted as a function of lead time of the forecast for light rain (trace, 1 mm h

– 1

) and moderate–heavy rain (more than 1 mm h

– 1

). Solid lines are objective forecasts without manual modification; dashed lines are subjective forecasts; numbers in parentheses denote number of cases. (b) The percentage error of the cases of moderate–heavy rain. Radar measurement errors found in the Dee Weather Radar Project (Harrold et al., 1974) are indicated, where BB stands for bright band. The performance of the Bellon and Austin (1984) cross-correlation technique is indicated by

Figure 8.5 (a) An example of a simple non-linear model that is much worse than a linear one. (b) An example of a very good non-linear model. Point C is the time a forecast is made for a period ending at point F. The dashed lines represent the actual behaviour of the rainfall; the dotted lines represent the model predictions of the rainfall; the solid line on the left-hand graph shows a simple linear prediction from point C

Figure 8.6 Sample of corresponding precipitation forecast products from UKV (left) and MOGREPS-UK (right), along with the verifying radar image (centre), for 0400Z on 25 November 2012. The MOGREPS-UK chart illustrates the ‘chance of heavy rain in the hour’, which is defined as 4 mm h

– 1

; members are the individual forecasts within the ensemble

Figure 8.7 Comparisons of: (a) the observed UK radar-derived surface precipitation rate at 15UTC 28 May 2012, with (b) the 5-hour forecast from the 10UTC Met Office 4D-Var hourly cycling 1.5 km NWP system, (c) the current operational nowcast from 10UTC using extrapolated radar derived rain rates blended with a 4 km resolution UK forecast from 03UTC, and (d) the latest available real-time forecast from the 3 hourly cycling with 3D-Var 1.5 km UK-wide system, which is a 12 hour forecast from 03UTC. The figure shows the comparison on the domain of the hourly cycling Met Office NWP system; the coastline is shown by the black contour

Figure 8.8 Schematic diagram of the different physical processes represented in the ECMWF IFS model

Figure 8.9 Resolution (solid) and reliability (dotted) components of the Brier skill score (vertical axis) for selected quantiles of local climatology: (a)

(b)

(c)

. Forecasts use the perturbed members from the ECMWF, Met Office and NCEP 15 day ensemble systems, and the simple aggregation of all these members (right panel). The spike in ECMWF reliability penalty at

days is associated with a coarsening of the model grid, and may be an artefact of the data interpolation code used

Chapter 09

Figure 9.1 Schematic representation of the structure of the SHE model

Figure 9.2 Grid cells and the transfer of water between grid cells

Figure 9.3 Example of the 10 day flow forecasts from the LISFLOOD-FF model for 1200UTC on 22 January 1995 for the Borgharen gauging station on the River Meuse, The Netherlands. The observed discharge is shown as a thick black line. The simulation is driven by the ECMWF TL511L60 deterministic forecast (shown as thick grey line) and the ensemble control forecasts. The ensemble forecast members are shown black

Figure 9.4 NFFS regional configuration and interaction (Deltares)

Figure 9.5 The grid-to-grid model structure

Figure 9.6 Several interquantile ranges together with 10 representative members for different catchment areas and different case studies: (a) Aare/Hagneck (5128 km

2

), (b) Reuss/Luzern (2251 km

2

), (c) Rhine/Rheinfelden (3455 km

2

), and (d) Rhine/Domat-Ems (3229 km

2

)

Chapter 10

Figure 10.1 Overtopping wave at Hartlepool, UK

Figure 10.2 Coastal flooding model categories; shortlisted categories are those considered to be practical and cost-effective for use in coastal flood forecasting

Figure 10.3 Integrated ‘cloud to coast’ ensemble modelling framework for coastal flood risk arising from overtopping and scour

Figure 10.4 Ensemble mean of wave height and direction predicted by the SWAN model at 43 m, 18 m and 10.5 m water depth at Newlyn Harbour, 27–30 October 2004; shaded area indicates one standard deviation about the ensemble mean denoted by lines of same shading; horizontal axis is UTC time

Figure 10.5 Cross-section of the building of the wave during a tsunami

Figure 10.6 Map of Indian Ocean tsunami 2004

Figure 10.7 Flooding on 5 December 2013 at the Marine Point development centred on the Caffe Cream in New Brighton, UK (

Liverpool Echo

, Trinity Mirror)

Figure 10.8 Damage caused to Aberystwyth (Wales) seafront after 5 January 2014 high tide (from

Daily Post North Wales

)

Figure 10.9 Flooding in 2008 in Venice, Italy

Chapter 11

Figure 11.1 The 1997 El Niño observed by TOPEX/Poseidon. The white areas off the tropical coasts of South and North America indicate the pool of warm water (NASA and CNES)

Figure 11.2 Long term Palmer drought severity index for the United States for week ending 9 August 2014, issued by the NOAA Climate Prediction Center (www.cpc.ncep.noaa.gov/products/analysis_monitoring/regional_monitoring/palmer/2014/08-09-2014.gif)

Figure 11.3 A dust storm approaching Rolla, Kansas, USA, 6 May 1935 (image: Franklin D. Roosevelt Library Digital Archives)

Figure 11.4 Mean annual precipitation over West Africa (in mm). The Sahel is indicated, showing the main area impacted by the drought of 2012

Chapter 12

Figure 12.1 A parcel of air

Figure 12.2 Schematic showing the balance of forces in an Ekman layer in the northern hemisphere at three levels from left to right: near the top, at mid-level and near the surface.

F

p

is pressure gradient force,

F

co

is Coriolis force,

F

vis

is frictional force and

V

is velocity

Figure 12.3 Hodograph of an Ekman layer driven by a geostrophic wind aloft

Figure 12.4 A discontinuity of density

Δρ

inclined at an angle

α

to the horizontal

Figure 12.5 Typical dimensions and simplified structure of a jet stream and wind speed blowing across it (into the paper); wind speeds are in knots

Figure 12.6 Diurnal wind change in coastal area

Figure 12.7 Pentad mean winds at 850 hPa over the Indian Ocean, 21–25 July 1988

Chapter 13

Figure 13.1 Idealized time series (curves A to D) of a representative parameter of a climatic element that is continuous in time (such as temperature or pressure). Vertical bars indicate arbitrary averaging or integrating periods (usually 30 years) which are recalculated each decade (see dashed bars) (after Hare, 1985)

Figure 13.2 Changes in global ice cover and northern hemisphere air temperatures north of 45

°

N over the last 150,000 years (after Mason, 1976)

Figure 13.3 Illustrating (a) temperature curve in China during the last 5000 years (after Chu, 1973); (b) 10 year running means of central England temperatures from 1650 to 1975 (after Manley, 1974); and (c) recorded changes in the annual mean temperature of the northern hemisphere since 1880 (after Budyko, 1969)

Figure 13.4 Power spectrum of the Manley record of central England temperatures with the long term trend removed (after Mason, 1976)

Figure 13.5 Changes in the atmospheric concentration of carbon dioxide (after Rotty and Weinberg, 1977)

Figure 13.6 Power spectrum of a time series of observations of the oxygen isotope content in a deep sea core from the equatorial Pacific which indicates fluctuations in global ice volume over the last 600,000 years (US National Academy of Sciences, 1975)

Figure 13.7 Maps of observed precipitation change over land from 1901 to 2010 (trends in annual accumulation) from one data set (from IPCC Fifth Assessment Report)

Figure 13.8 Illustrating 12 month running mean of global average temperatures from three data sets: HadCRUT3 (black and grey area) produced by the Met Office CRU; NCDC (dark grey) produced by the National Climate Data Center; and GISS (medium grey) produced by the Goddard Institute for Space Studies. The grey shaded area shows the approximate 95% confidence range for the HadCRUT3 data; the true global average is expected to lie outside this range around 5% of the time (from Defra/DECC, 2010)

Figure 13.9 Extremes in 1 day heavy precipitation, defined as the monthly averages that rank in the top or bottom 10th percentile of all data on record (after Lubchenco and Karl, 2012)

Figure 13.10 Changes in global ice cover, northern hemisphere air temperature (as in Figure 13.2), and total insolation north of 45

°

N over the last 150,000 years (after Mason, 1976)

Figure 13.11 Effects of deforestation on rainfall in the tropics. (a) Much of the rainfall over tropical forests comes from water vapour that is carried by the atmosphere from elsewhere. However, a large component is ‘recycled’ rain, that is water pumped by trees from soil into the atmosphere through evapotranspiration. Water exits from forests either as runoff into streams and rivers, or as vapour that is carried away by the atmosphere. The atmospheric transport of water vapour into the forest is balanced by exit of water in the form of vapour and runoff. (b) The analysis of Spracklen et al. (2012) suggests that deforestation reduces evapotranspiration and so inhibits water recycling. This decreases the amount of moisture carried away by the atmosphere, reducing rainfall in regions to which the moisture is transported. Decreasing evapotranspiration may also increase localized runoff and raise river levels (from Aragao, 2012)

Figure 13.12 The mean residence times of aerosols in different layers (after Flohn, 1973)

Figure 13.13 Conceptual scheme of the climate/water-resources relationship (after Novaky et al., 1985)

Figure 13.14 Changes in stream flow as a function of changes in precipitation and potential evapotranspiration (ETP). (a) Pease river at Vernon, Texas; drainage area 9034 km

2

; mean precipitation base 540 mm; mean runoff base 11 mm. (a) Leaf river near Collins, Mississippi; drainage area 1949 km

2

; mean precipitation base 1314 mm; mean runoff base 409 mm. (after Nemec, 1985)

Chapter 14

Figure 14.1 A vertical cross-section across the rural–urban boundary in West London, illustrating variation of the cloud base at the top of the boundary layer measured by Doppler lidar. The left-hand side of the image is over the rural area to the west, and the right-hand side of the image is over the urban area to the east. The colours represent the strength of Doppler radial velocities in m s

– 1

towards (positive) and away from (negative) the lidar. Above the boundary layer the colours represent noise in the measurements (from Collier et al., 2005)

Figure 14.2 How impervious cover affects the water cycle (from California Water Land Use Partnership, WALUP: www.coastal.ca.gov/nps/watercyclefacts.pdf)

Figure 14.3 Total summer rainfall (in centimetres) around St Louis, Missouri, USA during 2100–2400 CST in 1971–5. The shaded areas are major urban areas (labelled also ALN, EDW). Areas of high and low (relative to average) rainfall are indicated by H and L respectively (from Changnon and Huff, 1986)

Figure 14.4 Types of sewer systems: WWTP is wastewater treatment plant (from Design of Stormwater Tanks, Grundfos)

Figure 14.5 Interaction of surface and sewer flow (dual drainage concept) (from Schmitt et al., 2004)

Figure 14.6 Comparison of pre- and post-development flow conditions, Thompson Creek, Santa Clara Valley, California, USA, modelled for a 714 acre development (from California Water Land Use Partnership, WALUP: www.coastal.ca.gov/nps/watercyclefacts.pdf)

Figure 14.7 Impact of building on the local hydrologic cycle, illustrating the increase in surface runoff (after Maryland, USA, Department of the Environment)

Figure 14.8 Processes involved in deposition of atmospheric pollutants including acid rain (Smith, 1984)

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Advancing Weather and Climate Science Series

Series editor:John A. KnoxUniversity of Georgia, USA

Other titles in the series:

Meteorological Measurements and InstrumentationGiles HarrisonPublished: December 2014

Fluid Dynamics of the Mid-Latitude AtmosphereBrian J. Hoskins, Ian N. JamesPublished: October 2014

OperationalWeather ForecastingPeter Inness, University of Reading, UK andSteve Dorling, University of East Anglia, UKPublished: December 2012ISBN: 978-0-470-71159-0

Time-Series Analysis in Meteorology and Climatology: An IntroductionClaude Duchon, University of Oklahoma, USA andRobert Hale, Colorado State University, USAPublished: January 2012ISBN: 978-0-470-97199-4

The Atmosphere and Ocean: A Physical Introduction, 3rd EditionNeil C. Wells, Southampton University, UKPublished: November 2011ISBN: 978-0-470-69469-5

Thermal Physics of the AtmosphereMaarten H.P. Ambaum, University of Reading, UKPublished: April 2010ISBN: 978-0-470-74515-1

Mesoscale Meteorology in MidlatitudesPaul Markowski and Yvette Richardson, Pennsylvania State University, USAPublished: February 2010ISBN: 978-0-470-74213-6

Hydrometeorology

Christopher G. Collier

University of Leeds, UK

This edition first published 2016© 2016 by John Wiley & Sons, Ltd.

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Library of Congress Cataloging-in-Publication Data

Names: Collier, C. G., author.Title: Hydrometeorology / Christopher G. Collier.Description: Chichester, UK ; Hoboken, NJ : John Wiley & Sons, 2016. | Includes index.Identifiers: LCCN 2016007238| ISBN 9781118414989 (cloth) | ISBN 9781118414972 (pbk.)Subjects: LCSH: Hydrometeorology. | Hydrodynamic weather forecasting.Classification: LCC GB2801.7 .C65 2016 | DDC 551.57–dc23LC record available at http://lccn.loc.gov/2016007238

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Dedication

This book is dedicated with love and gratitude to Cynthia for all the support she has given to me over many years.

Series Foreword

Advancing Weather and Climate Science

Meteorology is a rapidly moving science. New developments in weather forecasting, climate science and observing techniques are happening all the time, as shown by the wealth of papers published in the various meteorological journals. Often these developments take many years to make it into academic textbooks, by which time the science itself has moved on. At the same time, the underpinning principles of atmospheric science are well understood but could be brought up to date in the light of the ever increasing volume of new and exciting observations and the underlying patterns of climate change that may affect so many aspects of weather and the climate system.

In this series, the Royal Meteorological Society, in conjunction with Wiley Blackwell, is aiming to bring together both the underpinning principles and new developments in the science into a unified set of books suitable for undergraduate and postgraduate study as well as being a useful resource for the professional meteorologist or Earth system scientist. New developments in weather and climate sciences will be described together with a comprehensive survey of the underpinning principles, thoroughly updated for the 21st century. The series will build into a comprehensive teaching resource for the growing number of courses in weather and climate science at undergraduate and postgraduate level.

Series Editors

Peter InnessUniversity of Reading, UK

John A. KnoxUniversity of Georgia, USA

Preface

The Earth, referred to as the blue planet, has three-quarters of its surface covered by water, which is essential to life. However, excessive variations bring disasters in the form of floods and droughts. Water is unevenly distributed in both time and space, and its circulation within the global atmosphere and oceans, the hydrological cycle, is a vital component of the earth’s energy system. Water is the medium through which the atmosphere has most influence on human wellbeing, and terrestrial surfaces have significant influence on the atmosphere. Early knowledge of water developed through local attempts to manage and control it.

Although atmospheric and hydrologic science and practice have largely developed separately, meteorological forecasts beyond a few days, and climate predictions, require numerical models that include realistic representations of surface hydrology and associated energy exchanges. Hence it is essential that hydrologists and meteorologists work together. Therefore the discipline of Hydrometeorology is important, and is addressed in this book. However, it is so wide ranging that this book cannot hope to cover everything, and at best I hope it stimulates the reader to investigate areas further.

Rainfall-runoff modelling at scales of interest (small to large catchments) is not able to reproduce all the details of flow processes that give rise to stream hydrology. Indeed it is essential to understand and articulate the uncertainties when addressing modelling problems. A wide range of numerical models have been developed to address river, surface and sewer flows. Also forecasts of rainfall and climate change are made using comprehensive models of the atmosphere at a range of grid scales depending upon the application from those appropriate to urban drainage systems to those appropriate to large continental river catchments. This work has been stimulated by the rapid advances in computer power over the last 30 years or so.

Remote sensing, both surface and space-based has been used for almost 80 years as a practical tool to aid mapping of river flood plain inundation areas and the earth’s surface. For many years most of the work has been qualitative. However the growth of both meteorological and hydrological sciences has demanded more comprehensive quantitative measurements. A range of instrumentation from simple raingauges and sophisticated weather radar to satellite passive radiometers and active radars underpin operational systems I examine how these trends have led to advances in hydro-meteorological studies.

I have included a wide range of both recent and historical references. Many of the earlier references remain very relevant to modern applications. The access to a wide range of literature via the internet and electronic databases enables the reader of this book to develop the knowledge contained therein. The book contains 14 chapters with each chapter ending with a summary of the main points in the chapter, a list of problems which readers may wish to use to test their appreciation of the contents and references. Each chapter also includes one or more appendices containing some additional information.

I wish to thank friends and colleagues who have encouraged me to work in the hydro-meteorological field. It is always difficult to engage with more than one discipline. However, I would highlight the scientific and practical benefits of the cross fertilization of ideas, and encourage young scientists in particular to accept the challenges that are offered by Hydrometeorology.

Chris G. CollierLeeds

Acknowledgements

I am very grateful to Audrie Tan, Delia Sandford, Brian Goodale and the editorial staff of Wiley for all their help in the preparation of this book. Appreciation of all the organisations and individuals who gave permission to use their material is acknowledged.

About the Companion Website

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www.wiley.com/go/collierhydrometerology

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Powerpoints of all figures from the book for downloading

PDFs of tables from the book

1The Hydrological Cycle

1.1 Overview

The hydrological cycle describes the continuous movement of water above, on and below the surface of the Earth. It is a conceptual model that describes the storage and movement of water between the biosphere (the global sum of all ecosystems, sometimes called the zone of life on Earth), the atmosphere (the air surrounding the Earth, which is a mixture of gases, mainly nitrogen (about 80%) and oxygen (about 20%) with other minor gases), the cryosphere (the areas of snow and ice), the lithosphere (the rigid outermost shell of the Earth, comprising the crust and a portion of the upper mantle), the anthroposphere (the effect of human beings on the Earth system) and the hydrosphere (see Table 1.1).

Table 1.1 Water in the hydrosphere and the distribution of fresh water on the Earth (from Martinec, 1985)

(a) Distribution of water in the hydrosphere

Forms of water present

Water volume (10

6

 km

3

)

As %

Oceans, seas

1348

97.4

Polar ice, sea ice, glaciers

28

2.0

Surface water, ground water, atmospheric water

8

0.6

Total

1384

100.0

Total fresh water

36

2.6

(b) Distribution of fresh water on Earth

Forms of water present

Water volume (10

6

km

3

)

As %

*

†

*

†

Polar ice, glaciers

24.8

27.9

76.93

77.24

Soil moisture

0.09

0.06

0.28

0.17

Ground water within reach

3.6

3.56

11.17

9.85

Deep ground water

3.6

4.46

11.17

12.35

Lakes and rivers

0.132

0.127

0.41

0.35

Atmosphere

0.014

0.014

0.04

0.04

Total

32.236

36.121

100.0

100.0

*Based on Volker (1970).

†Based on Dracos (1980), referred to in Baumgartner and Reichel (1975).

Models of the biosphere are often referred to as land surface parameterization schemes (LSPs) or soil–vegetation–atmosphere transfer schemes (SVATs). An example of an SVAT is described by Sellers et al. (1986). The water on the Earth’s surface occurs as streams, lakes and wetlands in addition to the sea. Surface water also includes the solid forms of precipitation, namely snow and ice. The water below the surface of the Earth is ground water.