11 trillion gallons of water needed in California?!

Yes! 11 trillion gallons of water is required regarding to the calculation from NASA satellite data (NASA news, 16 December 2014). If this number can not give you a specific idea, well, it means around 17 million full Olympic swimming pools. Such large amount required water seems hard to believe after severe floods and mudslides occurred in southern California (BBC news, 13 December 2014). So, what about droughts situation in California or U.S.? Does the drought get more severe? Just like the news what I found on the website that said the drought is the worst has seen in 1200 years in California (USA TODAY, 5 December 2014).

Figure1 the U.S. drought condition (Source: United States Drought Monitor)

After analysis among lots of indices such as SPI (standard precipitation index), NPP (net primary productivity) and NCE (net carbon exchange), Chen et al. 2012 indicates that there was no apparent change of droughts in southern U.S. from 1895 to 2007, although there was an increasing trend in drought intensity in many east regions. This change seems to bring a large loss to this area, as we can see from the resultant obviously drop in NNP which can even reach to 40% during extreme droughts (Chen et al. 2012). There is a wetting trend in most parts of U.S. according to the simulation of soil moisture and runoff except the southwest part in U.S. which has a few declining trend of soil moisture and runoff with increasing drought duration and severity (Andreadis and Lettenmaier 2006).

In regard to this opposite trend compared with the rest regions of the U.S., what might be the underlying reason? Kam et al. 2014 indicates that putting a positive phase of the AMO (Atlantic Multidecadal Oscillation) and a negative phase of the PDO (Pacific Decadal Oscillation) and ENSO (El Niño–Southern Oscillation) together, they would play a worse influence on droughts in the southern U.S. A continuous ridge of high atmospheric pressures generate offshore which would transfer storms track from California to Alaska during a majority of current winters may be the cause of droughts, because California gets most of precipitation in Decembers and Januaries (Dettinger and Cayan 2014). They also mentioned that droughts are going to be more severe and frequent due to climate change and there is a deep relationship between droughts and extreme storms in California. An increasing trend of temperatures results in the decreasing trend of mountain snowpack and earlier melting time of spring snow, which would play an important role in a declining trend of total precipitation (Seager and Vecchi 2010).

To sum up, California seems to be a special region in U.S. with different drought trends which  may be not very significant but still increasing and especially in duration and severity of droughts. In addition, there are several causes behind this trend. The first reason is the influence from the positive phase of the AMO, negative phase of the PDO and ENSO; The second is regarded as anomalous atmospheric pressure which further cause the change of storms; The third is global warming which bring effect on amount of snowpack and melting time.

The trend of droughts

IPCC SREX using the PDSI as an index to analyze the condition of observed global droughts and found there are still large uncertainties in  global scale trends. Dai 2012 argued that the prediction from model has consensus with the change of observed global dryness, which illustrate widespread and severe droughts over many regions in following 30-90 years due to declined precipitation and/or increased evaporation.

Figure1 Trend maps for precipitation and sc_PDSI_pm and time series of percentage dry regions. Long term trends during 1950-2010 in annual mean a. observed precipitation b. calculated sc_PDSI_pm using observation-based forcing c. smoothed time series of the drought regions

From Figure2, we can see that the PDSI_Th has a declining trend since 1970s, however this is not same as the PDSI_PM. As for the global area in drought during 1980-2008, the PDSI_Th has a significant increasing trend, although the trend of the PDSI_PM is not very obvious, it still has an increasing trend which is seven times smaller than the PDSI_Th (Sheffield et al. 2012).

Figure 2 Global average time series of the PDSI and area in drought. a, PDSI_Th (blue line) and PDSI_PM (red line). b, Area in drought (PDSI<-3.0) fro the PDSI_Th (blue line) and PDSI_PM (red line). Th: Thornthwaite algorithms. PM: Penman-Monteith algorithms.

However, Sheffield et al. 2012 argued that the PDSI derives from a simple water-balance model which is popular in large scale drought assessment but bring an overestimated result of global droughts and the trend of droughts has just changed a little over the past 60 years according to more further analysis. From paleoclimatic data, it can be found that recent droughts are not unparalleled because several severe megadroughts can be found in the paleoclimatic record (IPCC SREX).

Even regional droughts may bring some global impact, for example, the largest wheat producer and consumer in the world----China has to import grain due to a persistent drought in the northern growing area and world's largest wheat importer Egypt is having some economic and political problems resulting in dramatic increasing trend of food costs (Sternberg 2011).

Droughts

Floods and droughts seem to be two adverse extremes, so after exploring floods let’s turn to another type of natural disasters, droughts. It seems not hard to understand what the word “drought” means. We can easily get a picture in mind of dry earth with multiple deep cracks, withered crops and so on. IPCC Glossary makes a definition of drought: “A period of abnormally dry weather long enough to cause a serious hydrological imbalance.” However, IPCC SREX indicates that there are numerous definitions about drought which bring some difficulties to the research of drought. Heim Jr., 2002 describes droughts as four main categories: 

• meteorological (climatological) drought is an atmospheric condition with none or less than average precipitation
• agricultural drought makes a severe damage to crops although the deep layer of soil may contain adequate moisture
• hydrological drought refers to a persistent period of time of reducing water supply(surface or subsurface, e.g.: streamflow, lakes, reservoir and groundwater)
• socioeconomic drought relates to imbalance between demand and supply of some economic products affected by other three types of droughts

      

        Figure1 Contraction/Desiccation cracks in dry earth       Figure2 A livestock carcass in Marsabitm in northern Kenya,         (Sonoran desert, Mexico)                                                  which has suffered prolonged drought

Drought indices

Although there are some difficulties to explore the change of droughts, because of no consensus on the definition of drought and lack of observation data of soil moisture, there are some drought indices created to help us learn more about droughts.

Standard Precipitation Index (SPI) which is one of broadly used drought indices and solely based on standardized precipitation. The SPI consists of a transformation of long-term historic precipitation records to normal distribution with zero mean and standard deviation of unit (McKee et al., 1993). The SPI is appropriate for quantification of most categories of droughts, because of the strong relationship between itself and different elements (e.g. stream flow, ground water level, soil moisture content) on different time scale (Lloyd-Hughes and Saunders, 2002). Hayes et al., 1999 indicated advantages and disadvantages of the SPI. Three advantages: 1. Simplicity, based solely on rainfall; 2. Versatile, calculated on multiple timescales; 3. Normal distribution, consistent frequencies of severe and extreme drought classifications at any timescales and locations. Disadvantages: 1. depend on the quality of precipitation data; 2. limited data coverage; 3. timeliness of the preliminary data; 4. be misleading in regions with some seasonal rainfall regime; and other limitations.

Table1 Drought classification by SPI value and corresponding event probabilities

Consecutive Dry Days (CDD) is another widely used index which also only based on rainfalls, referring to maximum consecutive days with limited precipitation during a period of time below a certain threshold, typically 1 mm per day (Frich et al., 2002). The advantages of this indicator is that it can be used for a whole year or any seasons which you would like to choose (can see the example in Figure3).

Figure3 Projected annual and seasonal changes in dryness assessed for 2046-2065

(annual time scale) and 2081-2100(annual time scale and two seasons)

Palmer Drought Severity Index (PDSI) is different with two above indices because it considers not only precipitation, but also evapotranspiration. Dai, 2011 compared four forms of PDSI and  found them having a high correlation with soil moisture observation data in the US and Eurasia, also with yearly streamflow and land water storage respectively in most part of objective regions. It is a common index with some good properties, however there are also some limitations. It should be noted that PDSI is appropriate for central US, which means its less compatible property across different areas and over time (IPCC SREX). Therefore, when PDSI is applied for a certain region, it should be calibrated for local situation.

Here, I just make a introduction of these drought indices which are always seen in drought assessment articles. There are many other indicators, such as Precipitation Potential Evaporation Anomaly (PPEA) and Standardized Precipitation Evapotranspiration Index (SPEI). These indices have their own shortcomings and focus on just one or some aspects of droughts, therefore it is good choice to combine local properties to choose indices which can suit the objective region best. However, even though the projection is still not the completely right answer, because the change of environment. 

Losses from floods

Although the change of floods in global scale is still hard to make a certain conclusion, the increasing trend of socioeconomic losses from floods is in high confidence (IPCC WGIIAR5-Chap3). The risk of floods seems to link with numerous factors such as the exposure of population and assets to flood-prone regions, the development of a certain area and the situation of public infrastructures. The flood itself and some influence factors are difficult to make quantitative measurement, however, losses from floods are more easily calculated in comparison with above items. Kundzewicz et al., 2013 indicates that natural disasters related with extreme weather contribute to increasing economic losses. Figure1 clearly shows the upward trends of total and insured losses from floods during 1980 to 2012.

Figure1 Total and insured losses from flood disasters 1980–2012 (in 2012 values).

Considering the contribution of population growth, IPCC SREX analyzes the average physical exposure to river flooding in 60°N~60°S regions with catchments larger than 1000 km2 (areas limited by models). From Figure2, we can find that Asia is the most severe suffering area and affected population of Asia is distinctly larger than other areas. However, Africa has the most rapid growth rate of influenced people, which grows nearly 3.28 times by 2030 than in 1970. Europe and North America have first and second lowest growth rates of average physical exposures among all these regions, whose growth rates are 0.13 and 0.86 respectively. Moreover, Europe and North America are the only two areas whose growth rates under 1. Developing regions seem to suffer more losses than developed regions.

Figure2 Average physical exposure to floods assuming constant hazard (in thousands of people per year).

Above are all in global scale, IPCC SREX has further study in regional scale, choosing Europe as the research object. Figure3 illustrates that Northern and Southern Central Europe have obvious increasing in both expected affected people and economic damage. However, not all areas in Europe have an upward trend of flood risk, some parts of North Europe expected to suffer less during 2071~2100 than before.

Figure3 Impact of climate change by 2071–2100 on flood risk in Europe.

Models always have some limitations which lead to uncertainty of projection of exposed population towards floods. Hirabayashi et al., 2013 tried to use a number of models to make a projection and put all of them together to make a comparison. Although different models have different growth rates of flood exposure, all of them increase by 2100.

Figure4 Global flood exposure for the 20C 100-year flood, or above, in millions. 

The ensemble means of the historical simulations (thick black line) and the future simulations for each scenario (coloured thick lines). 

Not only some certain regions, but also the globe seem to have much losses in the future. The flood may be hard to control, but we can take measures to reduce damage such as relocating people in severe flood-prone regions, improving monitoring and post-disaster reconstruction systems and raising public awareness. I believe the more we do, the less damage we would suffer.

Floods and Climate Change

Thinking of the disastrous aftermath of floods, I would consider whether the incidence of floods get worse or not, especially under anthropogenic influence environment. Milly et al., 2002 pointed out that there is an increasing frequency of great floods mostly in northern high latitudes, which considered under climate change from anthropogenic radiative effects. They even made a projection of extratropical flood frequency using observed data and several models. Figure1 shows clearly about different start points of trends with statistical significance, and all trends from various models turn to be obvious at a certain year. But because of incomplete consideration of other possible forcing such as various land-use, some errors of models and other factors, the conclusion is tentative.

Figure1 Normalized trend of extratropical flood frequency for observations and for scenario experiments. 

                                    (Normalized trends greater than 1 imply significance with respect to this measure. 

                                     Bold curves: historical records; Light curves: continuing operation)

Hirabayashi et al., 2008 uses MIROC model to estimate the change of floods under global warming situation. There seems to be a link between flood frequency and river annual discharge. Increasing frequency of river floods accompanied by increasing annual discharge, but can not be inferred in reverse.

Floods

After several posts which talked about tropical cyclones, now let’s turn to another type of natural disasters Floods. Although it is a totally different type of natural disasters compared with tropical cyclones, it sometimes has close relationships with storms. So, I choose to explore secrets about Floods as the following part. 

But I should make it clear here that it does not mean all floods caused by tropical cyclones. Tropical cyclones is one of the reasons, sometimes, but not the only or necessary reason. Floods also come along with continuous heavy rains, large sea tidal surges, incompletely freeze/ thaw during winter/ spring or sudden destruction of some infrastructures such as dikes and dams. Furthermore, floods often lead to huge losses both in human life and economy. Let’s watch the general introduction video below to feel the tremendous power of floods.

A Big Hit----Hurricane Katrina

Although my hometown meet typhoon every year in summer, the aftermath from Hurricane Katrina still scared me. What a strong natural power!

Tropical cyclones and climate change

With the figure below, we will begin today’s journey about tropical cyclones and climate change. We can see clearly from this figure that western pacific has a high frequency of storms. The intensity (measured by minimum pressure) is lower over cooler water and close to equator, and higher over warmer water. (Mendelsohn et al., 2012)

Figure1 Storm tracks and minimum pressure for a sample of synthetic storms 

Knutson et al., 2010 indicates that Atlantic tropical cyclone power dissipation is statistical related to SST over the past 50 years. Figure2 shows this correlation between tropical atlantic ocean SST which  has more obvious growth than tropical mean SST and Atlantic power dissipation. The statistical correlation between power dissipation with low frequency variability and local SSTs in northwest Pacific Ocean is much weaker than for Atlantic Ocean. (Knutson et al., 2010)

Figure2 Past and extrapolated changes in Atlantic hurricane power dissipation index (PDI)

The relationship between western north Pacific Ocean and North Atlantic Oscillation (NAO) is a significant interdecadal change. Before the 1970s, they are in weak correlation which gradually change to positive and stronger, especially after 1980, the positive correlation is apparent at the 95% level. 1948-1977 is a weak phase of relationship between western north Pacific Ocean and NAO and 1984-2008 is a strong phase which of 0.48 coefficient is obvious at the 99% level. (Zhou & Cui, 2014)

Figure3 Running correlations between the NAOI and the WNPTCF in summer with a 25-year window width

Although the IPCC AR5 indicates that there is no significant trend of tropical cyclone activities in long term. And some researches even argued that global tropical cyclone activities decrease by 12.4 hurricanes per century with different decrease rates in northern hemisphere and southern hemisphere. Tropical cyclones attract lots of attentions from the public, because the huge damage of tropical cyclones influences human beings’ lives deeply. From figure4 (modeling future damage of tropical cyclones in 2100) we can see that the damage of tropical cyclones in different regions almost all increase, especially North America and East Asia. These regions occupy nearly 88% baseline global damage, because of more storms and lots in harm’s way. (Mendelsohn et al., 2012) And the rapid projected growth of economy in Asia and Central Amarica leads to significant growth of damage. Figure5 adds the impact from climate change, whose highest damage point is also North America with 26 billion dollars per year. And East Asia is the second highest damage region of 15 billion dollars per year, and Central America- Caribbean is the third one of 5 billion less than East Asia. (Mendelsohn et al., 2012) The damage is caused by various factors, not only natural factors, but also social factors. For example, the region in harm’s way or hit by tropical cyclones with high intensity are natural factors, whereas the rapid growth in economy or shift of population to coastal areas are social factors. (Mendelsohn et al., 2012)

Figure4 Present and future baseline tropical cyclone damage by region 

Figure5 Climate change impacts on tropical cyclone damage by region

Does the hurricane get worse than before?

It seems like that we hear about hurricane news more often than before. (Well, Hurricane Gonzalo has just gone, nearly two weeks ago.) Maybe many people hold the thought that the environment gets worse, and then extend the scope of this perspective to all branches such as the climate system, atmosphere and water cycle. How about hurricanes? Does it get worse than before?

Frequency of hurricanes

Global frequency
According to the conclusion of the latest IPCC report, it is in low confidence that changes of tropical cyclone activities are obvious in long term. From global time series pictures below, although the data set is limited, it can be seen that there is no significant trend of hurricanes’ occurrences from 1970 to 2004. Based on the scenario from Knutson et al. 2010, the projection shows that the global frequency of tropical cyclones maybe will keep generally still or decrease when average intensity increases by 2~11% and rainfall rates of tropical cyclones increase by nearly 20% within 100km of the cyclone centre. (IPCC chapter 14)

Global time series for 1970-2004 of number of storms

Regional frequency

But since 1970, some places have significant increasing trends of intense tropical cyclone activities, North Atlantic should be mentioned here. Webster et al. 2005 indicates that North Atlantic Ocean has an obvious increasing frequency in comparison with regional time series of other oceans. And this trend has a very high confidence level, which reaches at 99%. Based on time series of various cyclone indices including the duration, the power dissipation, the intensity and a compound of tropical cyclone frequency, since the late 1970s, the rising trend is presented in North Atlantic and the slight rising trend is found in western North Pacific. (IPCC chapter 2) What should be noted is that the trend of annual numbers of tropical cyclones is not robust, which has been observed over past one hundred years, as well as in North Atlantic. The annual regional frequency of tropical cyclones projection has similar trends with the annual global frequency, but has lower confidence level.(IPCC chapter 14)

Factors

The tropical cyclone is a complicated system, so it is influenced by a mix of natural and anthropogenic factors. IPCC AR4 (chapter 10) points out that anthropogenic factors more likely than not result in an upward trend in the intensity of tropical cyclones. Greenhouse gases increased by humanity affect the potential intensity of tropical cyclones, via leading to the change of Sea Surface Temperatures (SST). the SST is also influenced by the change of the radiation. Aerosols (including lots of types) also is a factor which influences different areas in different ways such as kinematics and thermodynamics. For example, in North Atlantic, the emission of pollution aerosols decreases which cause the increase of tropical Sea Surface Temperatures (SST) by changing cloud albedo. However, in northern Indian Ocean, the rising of aerosols lead to reduced vertical wind shear. It is still uncertain of the link between tropical cyclones and these factors.(IPCC chapter 14)

From above, the phenomenon, at least on global scale, may be not that terrible like some people think. Even though, we also need pay attention to hurricanes, because of the variability characteristics of them. 

Getting close to Hurricanes

Natural disasters contain plenty of adverse events, such as earthquakes, floods, tsunamis and tropical cyclones. When I was struggling to choose the natural disaster’s type in the first talk, I saw the news about Hurricane Gonzalo which hit UK this week. Thinking of last Tuesday’s heavy rains and strong winds, I decided to focus on Hurricanes firstly.

The remains of Hurricane Gonzalo will hit Britain

Hurricanes, Typhoons and Cyclones

I do not know whether you are confused about differences among hurricanes, typhoons and cyclones like me on the initial stage. I just want to make them clear on the beginning. Hurricanes, typhoons and cyclones are all the same weather phenomenon, only different depending on places where they occur. We call the storms as “Hurricanes” in the Atlantic and Northeast Pacific and use “Typhoons” and “Cyclones” to describe the same powerful storms in the South Pacific and Indian Ocean respectively. 

Super typhoons are so powerful they can be seen from space, as seen 

from this photo of Super Typhoon Bopha taken on Dec. 2.     

PHOTOGRAPH BY NASSA ISS/JSC

While the official hurricane season for the Atlantic Basin (the Atlantic Ocean, the Caribbean Sea, and the Gulf of Mexico) runs from 1 June to 30 November. As seen in the graph below, the highest point of whole year is 10 September, but even in December, hurricanes still can occur.

numbers of tropical cyclones per 100 years

Here I found two pictures about hurricanes’ history tracks. From pictures, we can see the prevailing tracks of hurricanes in North Atlantic and Eastern North Pacific. Most of hurricanes move towards west at first, when approach a certain extent of latitude they often move towards northeast.

 All North Atlantic and Eastern North Pacific hurricanes

(at least Category 1 on the Saffir-Simpson Hurricane Scale)

All North Atlantic and Eastern North Pacific major hurricanes

(at least Category 3 on the Saffir-Simpson Hurricane Scale)

The last graph I posted here is about numbers of hurricanes occurrence. As seen in this graph, the frequency of named cyclones occurrence has generally increased as time goes by, except several years (1887, 1915, 1933, 1936, 1968, 1994). But the tendency of hurricanes are not very obvious. Does the frequency of hurricanes occurrence change? If so, are there any influence factors? I will pay attention to these questions on the next post.

Bars depict number of named systems (open/yellow), hurricanes (hatched/green), 

and category 3 or greater (solid/red), 1886-2004 

In addition, I want to recommend some websites here:

• http://www.ready.gov/hurricanes

We can know some basic knowledge of various natural disasters on this website and what’s more we can find what we should do before, during and after these disasters.

• http://www.cyclonecenter.org/#/

It is an interesting and interactive website. We can learn more about cyclones and even predict future cyclone behavior there.

Introduction

Hello, everyone! Welcome to my little home online.

First of all, introduce myself. I am a postgraduate, studying in Climate Change. Last week, we were asked to set up a blog which is the assessment of this course. It’s a totally different assessment, and I never used a blog before. I am really nervous, but also excited.

When I first thought about the main topic of this blog, natural disasters occurred to me. Maybe you have never experienced them yourself, but I believe that instant news would not let you feel unfamiliar with them. 

Hurricane Katrina August 28 2005 NASA
by Jeff Schmaltz, MODIS Rapid Response Team, NASA/GSFC 

Lawine

My hometown is a small city on the southeast of China, along the coast, which is always hit by typhoons every summer. The strong wind, the heavy rain and the blown down trees. I have seen all of them, since I was a little child. Recent years, China went through a lot of natural disasters such as the 2008 Sichuan Earthquake, the 2008 Chinese winter storms, the 2010 China floods and the 2010 Yushu Earthquake. Although my hometown is nearly 1800km away from Sichuan, I still felt shaking (the ceiling lamp swung obviously in my high school) when the Sichuan Earthquake happened. In addition, I saw the destroyed scene after 2010 China floods in Jilin Province (where my university is located). Having experience on my own, I feel the power of natural disasters impressively. Therefore, I think it is a great opportunity for me to learn more about natural disasters which influence the globe deeply and interest me a lot.

ADBC Branch in BeiChuan after earthquake
by 人神之间 - Own work (Original text: self-made 自己制作)

During the following several months, I will focus on limited numbers of types of natural disasters. Exploring some questions which listed below:

• Are there any links between different types of natural disasters and environment change?
• Did these natural disasters become more extreme in recent decades?
• What we can do to face natural disasters? Positive or Negative?

I believe the blog will be better as the time goes by and I hope it will arouse your interests in this field as well. Your comments and supports are quite important to me. I am sorry that my english is not that good, so there may be some problems in expression. This is also a chance for me to improve my english. Please do not hesitate to let me hear your voices, even about spelling or grammar mistakes.