Posts Tagged ‘weather’
Wondering what global warming has to do with violent rainstorms, hurricanes, typhoons, cyclones and other enormous destructive and very wet (and cold) weather phenomena you may have experienced in 2012 September? Here is an answer, provided by the ever-watchful (and woefully under-appreciated) National Climatic Data Center of the USA’s National Oceanic and Atmospheric Administration (NOAA).
(1) The average combined global land and ocean surface temperature for September 2012 tied with 2005 as the warmest September on record, at 0.67°C (1.21°F) above the 20th century average of 15.0°C (59.0°F). Records began in 1880.
(2) The globally-averaged land surface temperature for September 2012 was the third warmest September on record, at 1.02°C (1.84°F) above average. The globally-averaged ocean surface temperature tied with 1997 as the second warmest September on record, at 0.54°C (0.97°F) above average.
(3) The average combined global land and ocean surface temperature for January–September 2012 was the eighth warmest such period on record, at 0.57°C (1.03°F) above the 20th century average.
This was the third warmest September over land in the Northern Hemisphere and fourth warmest in the Southern Hemisphere. In the higher northern latitudes, parts of east central Russia observed record warmth, as did parts of Venezuela, French Guiana, and northern Brazil closer to the tropics. Nearly all of South America was much warmer than average as were western Australia and central to eastern Europe. Far eastern Russia, a few regions in southern Africa, and parts of China were cooler than average.
Moreover, this was the second warmest summer (June–August) for Hungary since national records began in 1900; Australia experienced its third warmest September since records began in 1950, with the nationally-averaged maximum temperature 1.94°C (3.49°F) above the 1961–1990 average; in Argentina the monthly-averaged daily, maximum, and minimum temperatures were all above normal (and remember both Australia and Argentina are both wheat producers and exporters); Japan observed record warmth during September, the greatest warmth was observed across northern Japan (regions of Hokkaido and Tohuko), which was 3.7°C (6.7°F) above average; in Britain, the average September temperature was 0.7°C (1.3°F) below the 1981–2010 average and was the coolest September for the region since 1994 (that’s certainly linked to the Arctic sea ice melting at a record rate this year).
This set of images helps explain the worrying 2012 monsoon season in South Asia and why drought conditions are emerging in more districts with every passing week.
We are coming up to the eight-week mark of the 2012 monsoon (taking the 04-06 June date as the ‘normal’ for the monsoon to become active over south-west India, after which the climatological system slowly advances over the peninsula and up into northern India).
The Indian Meteorological Department (IMD) has not helped, by maintaining a scientific detachment between forecasting science and the dire situation of farmers and consumers. With emergency drought programmes new being rolled out in many states (more than a month late), the IMD’s refusal to speak plainly to those who need the information the most is unpardonable.
Worse, the Department on its website and its communications walls off its forecasting behind a very unfriendly science interface (see this commentary for a detailed explanation), and appears oblivious about its responsibilities to those for whom it exists – the citizens of India who are waiting for rain.
This set of images (strips below, you can click on the images for the full-size versions) describes what the IMD ought to be disseminating (but stubbornly refuses to). These are 24, 48, 72 and 96 hour regional forecasts for South Asia of accumulated precipitation and temperature extremes.
Day 1 – 02 Aug 2012
Day 2 – 03 Aug 2012
Day 3 – 04 Aug 2012
Day 4 – 05 Aug 2012
The four regions you see in the panels are Peninsular India and Sri Lanka, Western India and Pakistan, Northern & Central India and Nepal, and Eastern India and Bangladesh. These are from the monsoon forecasting sub-site of the Center for Ocean-Land-Atmosphere Studies – of the Institute of Global Environment and Society (IGES) – which processes and synthesises data from the NOAA/NCEP, which is the National Oceanic and Atmospheric Administration (NOAA, the US government agency), National Centers for Environmental Prediction. These regional weather forecasts are presented as a running four-day ensemble of images showing daily forecasts of 2-metre temperature minima and maxima and accumulated precipitation covering the four sub-regions.
The India Meteorological Department (IMD) has released the long-awaited update of its long range forecast for the 2012 monsoon.
Stripped of its scientific jargon, this is what the update has said. There is a July model and an August model. For both months, there are three forecast categories: below normal in which rainfall in less than 94% of the long period average (LPA), normal in which the rainfall is between 94% and 106% of the LPA, and above normal in which rainfall is more than 106% of the LPA. Under the three categories, the forecast probabilities for July are (in the same order) 36%, 41% and 23% and for August they are 42%, 36% and 22%. Under any combination of probability therefore, this means that both July and August are going to be drier than usual, and coming on top of an unusually dry June, the scenarios for water availability and for agriculture come early September are all looking tough.
The volatility of the 2012 monsoon over north-eastern India can be seen in the images of the district weekly rainfall deviations for those states. Please bear in mind that with the late beginning of the 2012 monsoon, the week of June from 07 to 13 was for all practical purposes the first monsoon week. The colours signify major deviations – red for 50% of the average and below, green for 150% of the average and above. In Arunachal Pradesh, for the first week the average rainfall in districts was around 45%, the second week it was 41% and the third week it shot up to 124% – red is evenly scattered through the districts in the first two weeks and green districts appear in the third week.
In Assam, the first week’s average for all the state’s districts was 65% of the long period average, with red dominating. In the second week the average was 103%, with ‘red’ districts declining and a few greens appearing. In the third week the average zoomed to 184% with most districts being ‘green’. In neighbouring Meghalaya, the average for the districts in the three weeks was 63%, then 51% and then a steep rise to 225% in the third week. In stark contrast Nagaland and Manipur have for the duration of these three weeks seen a combined district rainfall average of 33% and if we remove the ‘green’ districts from both states of the third week, we get a dismal 15% average – it is of course quite likely that there are data anomalies in the numbers that IMD has collected from the north-east region, as automated weather stations that actually work are likely to be fewer in number than in ‘mainland’ India. (There is a spreadsheet for this data. If you want the data till date please write to me here: makanaka at pobox dot com.)
In the update, there is also a separate set of forecasts and probabilities for four major regions of India – North-West India, Central India, South Peninsula and North-East India. There are small variations for each of these in the definitions of below normal, normal and above normal. Here are the forecast probabilities for the regions:
The list of states in each of these four geographical regions is:
Northwest India: Jammu and Kashmir, Himachal Pradesh, Punjab, Rajasthan, Haryana, Chandigarh, Delhi, Uttaranchal and Uttar Pradesh.
Northeast India: Arunachal Pradesh, Meghalaya, Assam, Nagaland, Manipur, Mizoram, Tripura, Sikkim, West Bengal, Bihar and Jharkhand.
Central India: Gujarat, Madhya Pradesh, Chattisgarh, Maharashtra, Goa and Orissa.
South Peninsula: Andhra Pradesh, Karnataka, Tamil Nadu, Kerala, Lakshadweep and Andaman and Nicobar Islands.
The first stage forecast for the nation-wide season rainfall was issued on 2012 April 26 and this update was issued on 2012 June 22. The summary of the first stage forecast is:
“Southwest monsoon seasonal rainfall for the country as a whole is most likely to be Normal (96-104% of Long Period Average (LPA)) with the probability of 47%. The probability (24%) of season rainfall to be below normal (90-96% of LPA) is also higher than its climatological value. However, the probability of season rainfall to be deficient (below 90% of LPA) or excess (above 110% of LPA) is relatively low (less than 10%). Quantitatively, monsoon season rainfall is likely to be 99% of the LPA with a model error of ± 5%. The LPA of the season rainfall over the country as a whole for the period 1951-2000 is 89 cm.”
The IMD has said that it has taken into account the experimental forecasts prepared by the national institutes like Space Applications Centre, Ahmedabad, Centre for Mathematical Modeling and Computer Simulation, Bangalore, Center for Development of Advanced Computing, Pune and Indian Institute of Tropical Meteorology, Pune. Operational/experimental forecasts prepared by international institutes like the National Centers for Environmental Prediction, USA, International Research Institute for Climate and Society, USA, Meteorological Office, UK, Meteo France, the European Center for Medium Range Weather Forecasts, UK, Japan Meteorological Agency, Japan Agency for Marine-Earth Science and Technology, Asian-Pacific Economic Cooperation (APEC) Climate Centre, Korea and World Meteorological Organization’s Lead Centre for Long Range Forecasting – Multi-Model Ensemble have also been taken into account.
In July 2011, the US National National Oceanic and Atmospheric Administration‘s (NOAA) National Climatic Data Center updated the Climate Normals for the USA.These are three-decade averages of weather observations, including temperature. The new annual normal temperatures for the United States reflect a warming world.
Following procedures set by the World Meteorological Organization, normals shift each decade, rather than each year. As of July 2011, the climate normals span 1981–2010, dropping the 1970s, which were unusually cool. Last year, the normals included 1971–2000, leaving out the warmest decade on record (2001–2010).
NASA’s Earth Observatory has provided maps which show the differences between the old normals and the new normals. The top image shows July maximum temperatures, and the lower image shows the January minimum temperatures.
Positive temperature changes appear in orange and red, and negative temperature changes appear in blue.
On average, the contiguous United States experiences the lowest temperatures on January nights, and the highest temperatures on July days. Both January minimum temperatures and July maximum temperatures changed, but not by equal amounts.
Parts of the Great Plains, Mississippi Valley, and the Northeast experienced slightly cooler July maximums from 1981–2010 compared to 1971–2000 (top map).
A much more striking difference, however, appears in the January minimums (lower map). Nighttime temperatures in January were higher everywhere except the Southeast. Warmer nights were especially pronounced in the northern plains through the northern Rocky Mountains—several degrees warmer in some places.
Comparing average temperatures year round, every state experienced warmer temperatures in 1981–2010 compared to 1971–2000.
NOAA’s National Climatic Data Center (NCDC) released the 1981-2010 Normals on July 1, 2011. Climate Normals are the latest three-decade averages of climatological variables, including temperature and precipitation. This new product replaces the 1971-2000 Normals product. Additional Normals products; such as frost/freeze dates, growing degree days, population-weighting heating and cooling degree days, and climate division and gridded normals; will be provided in a supplemental release by the end of 2011.
Although warmer temperatures can have benefits, they pose hazards to some plants. For instance, higher nighttime temperatures enable some pests—such as the pine bark beetle and wooly adelgid—to thrive in places where they previously froze.
What are Normals? – In the strictest sense, a “normal” of a particular variable (e.g., temperature) is defined as the 30-year average. For example, the minimum temperature normal in January for a station in Chicago, Illinois, would be computed by taking the average of the 30 January values of monthly-averaged minimum temperatures from 1981 to 2010. Each of the 30 monthly values was in turn derived from averaging the daily observations of minimum temperature for the station. In practice, however, much more goes into NCDC’s Normals product than simple 30-year averages. Procedures are put in place to deal with missing and suspect data values. In addition, Normals include quantities other than averages such as degree days, probabilities, standard deviations, etc. Normals are a large suite of data products that provide users with many tools to understand typical climate conditions for thousands of locations across the United States.
What are Normals used for? – Meteorologists and climatologists regularly use Normals for placing recent climate conditions into a historical context. NOAA’s Normals are commonly seen on local weather news segments for comparisons with the day’s weather conditions. In addition to weather and climate comparisons, Normals are utilized in seemingly countless applications across a variety of sectors. These include: regulation of power companies, energy load forecasting, crop selection and planting times, construction planning, building design, and many others.
The National Climatic Data Center compiles climate normals from observations from thousands of stations in the National Weather Service (NWS) Cooperative Observer Program, as well as stations staffed by professionals within the NWS, the National Oceanic and Atmospheric Administration (NOAA), and the Federal Aviation Administration.
Bangladesh, South Asia’s biggest rice buyer, is in talks with India to buy grains on a regular basis to bolster food security as governments seek to avoid a repeat of the unrest that broke out when prices last soared, reported Bloomberg.
A long-term agreement will protect Bangladesh from possible defaults by private traders, who sometimes fail to meet their commitments if prices gain, Muhammad Abdur Razzaque, the nation’s food minister, said in an interview yesterday. “Rice prices rose this year in our country; people are suffering as they have limited income,” Razzaque said by phone from Dhaka.
Bangladesh’s plan underscores a drive by governments to strengthen their reserves to help manage the impact of food prices that advanced to a record last month, beating the jump in 2008 that spawned riots from Haiti to Egypt. This year’s surge has driven millions into extreme poverty, according to the World Bank, and contributed to unrest in the Middle East and Africa. “When we go for international tenders and prices suddenly rise, private suppliers sometimes fail to fulfill their commitments,” Razzaque said. “They don’t supply us and put us in trouble. It has happened.”
In the Philippines, Sen. Francis Pangilinan, chairman of the Senate committee on agriculture, has called on the country’s Department of Agriculture (DA) and the Department of Trade and Industry (DTI) to start preparing for the worst-case scenario as far as the prices of oil and other basic commodities are concerned in response to the volatile situation in the Middle East.
The Philippine Star quoted Pangilinan as having said that other nations have started preparing for an expected food and oil shortage, not only because of the turmoil in the Middle East but also because of the erratic weather patterns that the world has been experiencing. “Some Asian governments have already started to come up with measures to mitigate rising prices. Erratic weather patterns have started wreaking havoc on our agricultural lands. China and India are stockpiling on grains, which means we need to rely less on importation to secure our buffer. The price of oil continues to soar, it is a matter that requires our serious attention,” he said.
In today’s world of interlinked markets, a problem in one place quickly ripples out to others. Croplands in Russia, one of the world’s leading wheat producers, were devastated by fires during last summer’s record-breaking heat wave. Wheat harvests in Ukraine, also plagued by torrid weather, dropped 15 percent last year, a comment in Radio Free Europe/Radio Liberty reminded readers.
Both countries responded by introducing export bans that have exacerbated global shortages of the commodity. Partly as a result, world wheat prices doubled between June 2010 and January 2011. According to the World Bank, wheat prices have risen in the past six months by 54 percent in Kyrgyzstan, 45 percent in Bangladesh, and 33 percent in Mongolia.
In the oil-rich Caucasus republic of Azerbaijan, high prices have been sending citizens across the border into neighboring Georgia, where they are buying up meat, potatoes, onions, and apples. Nadeem Ilahi, head of an International Monetary Fund (IMF) delegation visiting Baku this week, warned that Azerbaijanis should expect overall prices to rise 10 percent in the course of this year — most of it due to the worldwide rise in the cost of food.
From late 2003 to early 2005 I was part of a small group in south Nagaland (in India’s north-east region) conducting a study on natural resource management and the prospects for tourism in the region. The study was funded by a Indian central government ministry, was ‘supervised’ by the state government and was made possible by the village community of Khonoma, in the Naga hills.
At around the mid-point of our study, when the time had come for the paddy seedlings to be transplanted, that the convergence of climate change and scarce labour resources became obvious. The seedlings were not ready to be moved at the time of year they were usually expected to be. By the time they were, the extra labour each rice farming family had mobilised in preparation for the hard work ahead, had their regular jobs and occupations to return to. The hill villages were in turmoil. Practically every single family that had a plot of terraced rice field to attend to was caught in a dilemma.
If they insisted that those who had come to the villages to help them – daughters, sons, cousins or aunts – stay back to complete the work, those helpful souls would certainly lose salaries and wages. If they let them return, they would have to look for very scarce hired labour, whose per day wage was high and which would certainly rise given the scarcity of hands available and time. It was for most families a Hobson’s choice, and by either reckoning only made the socio-economic cost of rice cultivation dearer. This was the most dramatic impact of climate change that I saw at the time, for the shift in transplanting season was considered very odd indeed by the villages, almost unprecedented.
We know now that local observations of direct effects of climate change by tribal populations and indigenous peoples corroborate scientific predictions. In a very real sense, indigenous peoples are the advance guard of climate change. They observe and experience climate and environmental changes first-hand, and are already using their traditional knowledge and survival skills – the heart of their cultural resilience – to respond. Moreover, they are doing this at a time when their cultures and livelihoods are already undergoing significant stresses not only due to the environmental changes from climate change, but from the localised pressures and economic impulses of global trade and movement of capital.
The United Nations University’s Institute of Advanced Study has just released an advance copy of what promises to be a goldmine of such observation. The volume is entitled ‘Advance Guard: Climate Change Impacts, Adaptation, Mitigation and Indigenous Peoples – A Compendium of Case Studies’. The 402 case studies summarised in this densely packed volume mention a host of specific vulnerabilities and early effects of climate change being reported by indigenous peoples (and these include cultural and spiritual impacts): demographic changes, including displacement from their traditional lands and territories; economic impacts and loss of livelihoods; land and natural resource degradation; impacts on food security and food sovereignty; health issues; water shortages; and loss of traditional knowledge.
Impacts are felt across all sectors, including agriculture and food security; biodiversity and natural ecosystems; animal husbandry (particularly pastoralist lifestyles); housing, infrastructure and human settlements; forests; transport; energy consumption and production; and human rights. The entire range of effects on habitats and their biomes are supplied: temperature and precipitation changes; coastal erosion; permafrost degradation; changes in wildlife, pest and vector-borne disease distribution; sea-level rise; increasing soil erosion, avalanches and landslides; more frequent extreme weather events, such as intense storms; changing weather patterns, including increasing aridity and drought, fire and flood patterns; and increased melting of sea-ice and ice-capped mountains.
“In spite of these impacts,” states the UNU-IAS compilation, “indigenous peoples also have a variety of successful adaptive and mitigation strategies to share. The majority of these are based in some way on their traditional ecological knowledge, whether they involve modifying existing practices or restructuring their relationships with the environment. Their strategies include application and modification of traditional knowledge; shifting resource bases; altering land use and settlement patterns; blending of traditional knowledge and modern technologies; fire management practices; changes in hunting and gathering periods and crop diversification; management of ecosystem services; awareness raising and education, including use of multimedia and social networks; and policy, planning and strategy development.”
From Asia, I’ve picked out three cases which illustrate just how important it is to observe and learn from these responses:
BANGLADESH | Indigenous forecasting in Maheshkhali, using meteorological indicators and animal behaviour to predict cyclones. Maheshkhali Island is situated off the Bay of Bengal coast with an area of approximately 60 square km. Cyclones are the greatest disaster threat of coastal people. Research has revealed that certain indigenous prediction capacity possessed by the local people always helped them to anticipate cyclones and take necessary precautions. The indigenous cyclone prediction is even more important as it was revealed during interviews with the Maheskhali islanders that they do not understand the modern warning system with its different numerical codes (1-10) and elaboration on wind direction, as explained in the warning bulletins.
INDIA | Indigenous forecasting in India using meteorological indicators, plant features and animal behaviour. Researchers from Gujarat Agricultural University have evaluated eight indigenous forecasting beliefs between 1990 to 1998. For each year, the data was tabulated and analysed on the basis of Bhadli’s criteria. Based on the findings the researchers concluded that many of the beliefs are reliable indicators of monsoon. The study has helped to restore the people’s confidence in their own traditional knowledge and skills. As climate change occurs, these traditional forecasting indicators may change. Locals have to continue their observations and adjust their predictions accordingly to ensure that correct coping mechanisms will be applied.
INDONESIA | Customary Iban Community. This study examines the social and institutional practices of a sedentary Iban sub-tribe in the upstream part of the Kapuas system in governing their life. In 2008, the Sungai Utik community acquired a formal, recognition of their institutional capacity to live at the center of one of the most complex ecosystems that is the tropical rainforest of Kalimantan. The Indonesian Eco-label Institute provided the community logging practice of the Sungai Utik Ibans its “seal of ecological appropriateness”. The Sungai Utik life-space is part of the bigger climatic zone just north of the Equator that has been predicted to experience higher precipitation over the course of climate change in this century, particularly in comparison with the last three decades of the last century. It means that the community should learn to adapt to a transformed rainy season—the duration of which and the timing of its start and ending are also subject to change—for the crucial nugal (planting) rituals.