Misreading monsoon

As usual in May, there is a welter of forecasts and opinions about the monsoon, the great majority of which are short on understanding and shorter on elementary science. The media – newspapers, television news channels, their websites – are to blame for spreading half-baked forecasts and wild prognoses. Not one of the numerous newspapers and TV channels, whatever the language they employ, bother to provide their reporters a basic grounding in the climatological system that gives us our monsoon.

In the first place, the India Meteorological Department (IMD) issues an operational forecast for the south-west monsoon season (June to September) rainfall for the country as a whole in two stages. The first stage forecast is issued in April and the second stage forecast is issued in June. These forecasts are prepared using state-of-the-art Statistical Ensemble Forecasting system (SEFS) and using the dynamical coupled Ocean-Atmosphere global Climate Forecasting System (CFS) model developed under Monsoon Mission of the Ministry of Earth Sciences.

On 15 April 2019 the IMD issued its first stage forecast. Based on our own in-field observations from the west coast, from the patterns of maximum termperature bands and variations in the lower and central peninsular region, from the sea surface temperatures in the Arabian Sea particular its southerly reaches and ditto for the Bay of Bengal, and from the wind patterns that can be experienced at various places in the peninsula and on the west coast, we find the IMD first stage forecast to be reliable.

It is the chronically ignorant media – which over the last few years has displayed a tendency to prefer some so-called private sector weather forecasters instead of what the Ministry of Earth Sciences provides – found irresponsibly claiming that the monsoon of 2019 will be ‘deficient’ and will also begin ‘late’. Neither of these terms is sensible in any way, and we take no satisfaction in noting that only a media that is insensible to planetary and mesoscale events like climate, will employ such insensible terms in reporting that is meant to educate and benefit the public.

IMD’s April forecast used the following five predictors: 1. the Sea Surface Temperature (SST) Gradient between North Atlantic and North Pacific (in December and January), 2. the Equatorial South Indian Ocean SST (in February), 3. the East Asia Mean Sea Level Pressure (in February and March), 4. North-west Europe Land Surface Air Temperature (in January), and 5. Equatorial Pacific Warm Water Volume (in February and March).

There are two forecasts the IMD makes. One is based on the Monsoon Mission CFS Model, which considers global atmospheric and oceanic initial conditions up to March 2019 and use 47 ensemble members (or kinds of data). The forecast based on the CFS model suggests that the monsoon rainfall during the 2019 monsoon season (June to September) averaged over the country as a whole is likely to be 94% ± 5% of the Long Period Average (LPA).

The second is the forecast based on the operational Statistical Ensemble Forecasting system (SEFS). This shows that quantitatively, the monsoon seasonal rainfall is likely to be 96% of the Long Period Average (LPA) with a model error of ± 5%. The SEFS comprises five category probability forecasts for the June to September rainfall over the country as a whole:

Overall therefore the IMD forecast is for the 2019 monsoon rainfall to be near normal. The IMD has already pointed out (which can be seen from the probabilities of the categories given in the table) that there is only a small chance for the monsoon rainfall to be above normal or excess. In view of the weather events and the climatological changes that we are seeing from day to day in May, ascribing a ‘lateness’ to the monsoon is absurd. Monsoon conditions already exist in and over the Indian land mass and in and over the great watery zones extending southwards from latitude 8 degrees North – and that is why we will find rain-bearing clouds crossing the south-western coastline in the first week of June 2019.

(Reposted from India Climate Portal.)

A method for a post-carbon monsoon

The uses to which we have put available climatic observations no longer suit an India which is learning to identify the impacts of climate change. Until 2002, the monsoon season was June to September, there was an assessment in May of how well (or not) the monsoon could turn out, and short-term forecasts of one to three days were available only for the major metros and occasionally a state that was in the path of a cyclone. But 2002 saw the first of the four El Niño spells that have occurred since 2000, and the effects on our Indian summer monsoon began to be felt and understood.

The India Meteorology Department (which has become an everyday abbreviation of IMD for farmers and traders alike) has added computational and analytical resources furiously over the last decade. The new research and observational depth is complemented by the efforts of a Ministry of Earth Sciences which has channelled the copious output from our weather satellites, under the Indian Space Research Organisation (ISRO), and which is interpreted by the National Remote Sensing Centre (NRSC), to serve meteorological needs.

The IMD, with 559 surface observatories, 100 Insat satellite-based data collection platforms, an ‘integrated agro-advisory service of India’ which has provided district-level forecasts since 2008, a High Performance  Computing  System commissioned in 2010 (whose servers run at Pune, Kolkata, Chennai, Mumbai, Guwahati, Nagpur, Ahmedabad, Bengaluru, Chandigarh, Bhubaneswar, Hyderabad and New Delhi) ploughs through an astonishing amount of numerical data every hour. Over the last four years, more ‘products’ (as the IMD system calls them) based on this data and its interpretation have been released via the internet into the public domain. These are reliable, timely (some observation series have three-hour intervals), and valuable for citizen and administrator alike.

The new 11-grade indicator for assessing weekly rainfall departures in districts. Same data, but dramatically more useful guidance.

Even so, the IMD’s framing of how its most popular measures are categorised is no longer capable of describing what rain – or the absence of rain – affects our districts. These popular measures are distributed every day, weekly and monthly in the form of ‘departures from normal’ tables, charts and maps. The rain adequacy categories are meant to guide alerts and advisories. There are four: ‘normal’ is rainfall up to +19% above a given period’s average and also down to -19% from that same average, ‘excess’ is +20% rain and more, ‘deficient’ is -20% to -59% and ‘scanty’ is -60% to -99%. These categories can mislead a great deal more than they inform, for the difference between an excess of +21% and an excess of +41% can be the difference between water enough to puddle rice fields and a river breaking its banks to ruin those fields.

In today’s concerns that have to do with the impacts of climate change, with the increasing variability of the monsoon season, and especially with the production of food crops, the IMD’s stock measurement ‘product’ is no longer viable. It ought to have been replaced at least a decade ago, for the IMD’s Hydromet Division maintains weekly data by meteorological sub-division and by district. This series of running records compares any given monsoon week’s rainfall, in a district, with the long period average (a 50-year period). Such fineness of detail must be matched by a measuring range-finder with appropriate  interpretive indicators. That is why the ‘no rain’, ‘scanty’, ‘deficient’, ‘normal’ or ‘excess’ group of legacy measures must now be discarded.

In its place an indicator of eleven grades translates the numeric density of IMD’s district-level rainfall data into a much more meaningful code. Using this code we can immediately see the following from the chart ‘Gauging ten weeks of rain in the districts’:

1. That districts which have experienced weeks of ‘-81% and less’ and ‘-61% to -80%’ rain – that is, very much less rain than they should have had – form the largest set of segments in the indicator bars.

2. That districts which have experienced weeks of ‘+81% and over’ rain – that is, very much more rain than they should have had – form the next largest set of segments in the indicator bars.

3. That the indicator bars for ‘+10% to -10%’, ‘-11% to -20%’ and ‘+11% to +20%’ are, even together, considerably smaller than the segments that show degrees of excess rain and degrees of deficient rain.

Far too many districts registering rainfall departures in the categories that collect extremes of readings. This is the detailed reading required to alert state administrations to drought, drought-like and potential flood conditions.

Each bar corresponds to a week of district rainfall readings, and that week of readings is split into eleven grades. In this way, the tendency for administrations, citizens, the media and all those who must manage natural resources (particularly our farmers), to think in terms of an overall ‘deficit’ or an overall ‘surplus’ is nullified. Demands for water are not cumulative – they are made several times a day, and become more or less intense according to a cropping calendar, which in turn is influenced by the characteristics of a river basin and of an agro-ecological zone.

The advantages of the modified approach (which adapts the Food and Agriculture Organisation’s ‘Global Information and Early Warning System’ categorisation, designed to alert country food and agriculture administrators to impending food insecurity conditions) can be seen by comparing the single-most significant finding of the IMD’s normal method, with the finding of the new method, for the same point during the monsoon season.

By 12 August 2015 the Hydromet Division’s weekly report card found that 15% of the districts had recorded cumulative rainfall of ‘normal’ and 16% has recorded cumulative rainfall of ‘deficient’. There are similar tallies concerning rainfall distribution – by region and temporally – for the meteorological sub-divisions and for states. In contrast the new eleven-grade measure showed that in seven out of 10 weeks, the ‘+81% and over’ category was the most frequent or next-most frequent, and that likewise, the ‘-81% and less’ category was also the most frequent or next-most frequent in seven out of 10 weeks. This finding alone demonstrates the ability of the new methodology to provide early warnings of climatic trauma in districts, which state administrations can respond to in a targeted manner.

Mapping climate behaviour, ten days at a time

This year, the Global Information and Early Warning System (GIEWS, a project of the FAO) has brought into public domain a new rainfall and vegetation assessment indicator. The indicator takes the form of maps which describe conditions over blocks of ten days each, with each such block termed a dekad (from the Greek for ‘ten’). Thus we have visual views of divisions of thirds of a month which from a crop cultivation point of view, now lies between the weekly and fortnightly assessments regularly provided by agri-meteorological services.

How to read the colours used in the rainfall anomaly maps.

In 2015, what was quickly called “out of season” rainfall was experienced in most of India during March and April. These conditions carried over into May and that is why the typical contrast between a hot and rainless May and a wet June is not seen.

The panel of maps shows the incidence of normal, below normal and above normal rain during six dekads of May and June. Greens signal above normal, yellows are normal and reds are below normal. The first dekad of May looks like what the second week of June normally does, but for the large above normal zone in the north-central Deccan. The second dekad of May has in this set had the largest number of above normal points, with more rain than usual over the southern peninsula, and over Chhattisgarh, Odisha, West Bengal. Rajasthan and Punjab.

The third dekad of May shows most of India as far below normal. This changes in the first dekad of June, with rain over the eastern coast registering much above normal for the period – Tamil Nadu, Rayalaseema, Andhra Pradesh and Odisha. During the second dekad of June, the divide north and south of the Vindhyas is visible, when northern India and the Gangetic belt continued to experience very hot days whereas over Telengana, Karnataka, Vidarbha and Madhya Maharashtra there was above normal rainfall. During the third dekad of June the picture was almost reversed as the southern states fell below their running rainfall averages.

This panel describes not rainfall but the anomalies (above and below) recorded in received rainfall. At the level of a meteorological sub-division or a river basin, the anomaly maps are a quick and reliable guide for judging the impacts of climate variability on crop phases (preparation, sowing, harvest) and on water stocks.

Monsoon 2015 could be 93% with ifs and buts

The India Meteorological Department has just released it’s long-awaited forecast for the 2015 Indian monsoon. In terms of the quantity of rainfall over the duration of the monsoon season (June to September) the IMD has said it will be 93% of the ‘Long Period Average’. This average is based on the years 1951-2000.

What this means is the ‘national’ average rainfall over the monsoon season for India is considered to be 89 centimetres, or 890 millimetres. So, based on the conditions calculated till today, the ‘national’ average rainfall for the June to September monsoon season is likely to be 830 millimetres.

There are caveats and conditions. The first is that the 93% forecast is to be applied to the long period average for each of the 36 meteorological sub-divisions, and a ‘national average’ does not in fact have much meaning without considerable localisation. The second is that the forecasting methodology itself comes with a plus-minus caution. There is “a model error of ± 5%” is the IMD’s caution.

This first forecast and the model that the forecast percentage has emerged from are thanks to the efforts of the Earth System Science Organization (ESSO), under the Ministry of Earth Sciences (MoES), and the India Meteorological Department (IMD), which is the principal government agency in all matters relating to meteorology. This is what the IMD calls a first-stage forecast.

As with all complex models, this one comes with several considerations. The ESSO, through the Indian Institute of Tropical Meteorology (IITM, which is in Pune), also runs what it calls an ‘Experimental Coupled Dynamical Model Forecasting System’. According to this, the monsoon rainfall during the 2015 monsoon season (June to September) averaged over India “is likely to be 91% ±5% of long period model average”. (The IMD forecast is available here, and in Hindi here.)

This is a lower figure than the 93% headline issued by the IMD. This too should be read with care as there are five “category probability forecasts” that are calculated – deficient, below normal, normal, above normal and excess. Each is accompanied by a forecast probability and a climatological probability (see the table). The maximum forecast probability of 35% is for a below normal monsoon, while the maximum climatological probability is for a normal monsoon.

As before, time will tell and the IMD will issue its second long range forecast in June 2015. Our advice to the Ministry of Earth Sciences and to the IMD is to issue its second long range forecast a month from now, in May, and also to confirm these forecasts two months hence in June, when monsoon 2015 will hopefully be active all over the peninsula. [This is also posted on India Climate Portal.]

Why IMD’s rain math doesn’t add up

Each blue bar represents the actual rainfall recorded by a district as a percentage of its normal. There are 614 district recordings in this chart.. The red dotted line is the 100% mark, and many of the bars end below, or way below, this mark. This is the district-level view of cumulative rainfall over eight rain weeks using the IMD’s own data.

Over eight weeks of recorded monsoon rain, the district-level data available with the India Meteorological Department (IMD) portrays a picture that is very different from its ‘national’ and ‘regional’ advice about the strength and consistency of rainfall.

In its first weekly briefing on the monsoon of August 2014, IMD said: “For the country as a whole, cumulative rainfall during this year’s monsoon (01 June to 30 July 2014) has so far upto 30 July been 23% below the Long Period Average.” Out of 36 meteorological sub-divisions, said the IMD, the rainfall has been normal over 15 and deficient over 21 sub-divisions.

The four regional readings that make IMD’s data look less worrisome than it actually is.

However, here is a far more realistic reading of the monsoon season so far, from the IMD’s own data. For the 614 individual readings from districts that have regular rainfall readings, we have the following: 86 districts have registered scanty rainfall (-99% to -60%); 281 districts have registered deficient rainfall (-59% to -20%); 200 districts have registered normal rainfall (-19% to +19%); and 47 districts have registered excess rainfall (+20% and more).

What this means, and the chart I have provided to illustrate the 614 individual values leaves us in no doubt, is that 367 out of 614 districts have had meagre rain for eight weeks. This also means that over eight weeks where there should have been rainfall that – as the IMD predicted in early June – would be around 95% of the ‘long period average’, instead three out of five districts have had less than 80% of their usual quota.

Monsoon 2014 and a third dry week

05 to 11 June is the first week. 12 to 18 June is the second week. 19 to 25 June is the third week. The bars represent the weeks and are divided by IMD’s rainfall categories, with the length of each category in a bar showing the proportion of that category’s number of districts. The colours used here match those used in IMD’s weekly rainfall map (below) which displays the category-wise rainfall in the 36 meteorological sub-divisions (but not by district).

IMD’s weekly rainfall chart, 19 to 25 June

We now have rain data for three complete weeks from the India Meteorological Department (IMD) and for all the districts that have reported the progress of the monsoon.

The overall picture remains grim. In the third week of the monsoon the number of districts that reported normal rains in that week (-19% to +19% of the average) is only 74. No rain (-100%) was reported by 71 districts Scanty rain (-99% to -60%) was reported by 221 districts, deficient rain (-59% to -20%) was reported by 125 districts, excess rain (+20% and more) was reported by 129 districts, and there was no data from 21 districts.

The Department of Agriculture and Cooperation, of the Ministry of Agriculture, has already issued its guidance to states on the contingency plans to be followed for a delayed monsoon. That is why it is important to make available the district-level normals and rainfall departures – the meteorological sub-divisions are too broad for such analysis and are irrelevant to any contingency plans and remedial work.

By end-June, when the IMD updates its outlook for the rest of monsoon 2014, we expect more detailed assessments of the districts to be publicly available – the agromet (agricultural meteorology section) already provides this to the states, with state agriculture departments given the responsibility of ensuring that the advice – which is especially important for farmers to plan the sowing of crop staples – reaches every panchayat.

The 6 June water event that our planners have missed

This was in January 2013, in Mysore district, Karnataka. Can these women even use their coracle today?

In just under six weeks from today, the water available per head in India from our major reservoirs will drop under the 100 litres per day mark. This will happen on or around 06 June 2013, give or take a day.

Two charts with water levels for half the 84 major reservoirs, early February to late April 2013. Data taken from CWC

For India’s 59 cities with populations of over a million (this will be so in mid-2013, see ‘India in 2015 – 63 million-plus cities’) this will mean an ever more frantic and dangerous race to secure water stocks by urban water mafia, who plunder public water storage and groundwater aquifers alike.

In the largest of these cities, their water boards claim to supply between 160 and 200 litres per capita per day (lpcd). This amount is roughly in line with what residents in comparably large East and South-East Asian cities are supplied, and is well above the lower end (100 lpcd) offered by the World Health Organisation as the minimum ‘optimal’ daily water stock required by an individual to maintain health and hygiene (100-200 lpcd is the band).

That’s the WHO view, but even in the Tenth Five Year Plan (2002-07) it was recommended that in India’s largest metropolitan cities the minimum must be 150 lpcd and in large non-metro cities the minimum must be 135 lpcd.

But six weeks from now, judging by the rate at which water has been used in 2013 from the 84 major reservoirs, we are not going to have, per head per day, even 100 litres of water. (Also see ‘Big dams, scarce water, thirsty India, uncertain monsoon’.)

Two more charts with water levels for the rest of the 84 major reservoirs, early February to late April 2013. For both sets of charts, the trendlines describe water volume as a per cent of the full reservoir volume. Data taken from CWC

How did we get here, so quickly and so dry? On 14 February 2013, the total water stored in the 84 major reservoirs was 68.718 billion cubic metres (bcm). Over the next ten weeks, until 25 April 2013, that total has dropped steeply to 42.304 bcm.

The Central Water Commission monitors the levels of and volumes in these 84 reservoirs, which if they all were full would store 154.421 bcm. These 84 reservoirs, says the CWC, represent 61% of the country’s water stored in reservoirs, which is altogether 253.388 bcm.

Judging by the same rate of water drawal from these 84 reservoirs, we have used over 43 bcm from all reservoirs in ten weeks, depleting our reservoir stock from 112.6 bcm to 69.3 bcm. This also means that in early February 2013, each of us were (notionally) holding a water stock of about 247 litres per day, a stock that was shrinking at a rate of about 1.3 litres per day to reach 152 litres per day in late April. And remember this is notional water stock per head from reservoirs, water that is used for agriculture and industry too.

What will happen between now and 06 June, when that individual stock drops under 100 lpcd? The Indian Meteorological Department has claimed (the usual bland and bored claim, as if monsoon was just another filing cabinet) that we will have a normal monsoon. As usual, the IMD has made no effort to link water with our alarming depletion of litres per head per day (it does link monsoon with GDP though, typically correct politically, typically unconcerned about human, animal and ecosystem need).

And what if the monsoon is late, scanty or erratic, as has happened with every monsoon since 2009? The IMD doesn’t know, your city’s PWD and municipality don’t know. But the water mafia do, and they’re getting very busy.

Will it or won’t it? India’s monsoon forecast gamble

Assam flood refugees. Photo: Alertnet

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.

Arunachal Pradesh district rainfall for three weeks

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.

Assam districts rainfall for three weeks

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.)

The first three weeks of monsoon 2012 in district averages for Nagaland, Manipur, Mizoram and Meghalaya

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.

Alarming reds and yellows over southern, central and northern India, threatening blues in north-eastern India (Bangladesh has been hit hard by floods). Graphic: IMD

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.

Climate change in the USA and the new plant growers’ map

The US government’s map of planting zones, usually seen on the back of seed packets, has changed. An update of the official guide for gardeners reflects a new reality, that of climate change and shifting meteorological zones. Some plants and trees that once seemed too vulnerable to cold can now survive farther north than they used to.

As this report on Yahoo News pointed out, it’s the first time since 1990 that the US Department of Agriculture (USDA) has updated the map and much has changed. Nearly entire states, such as Ohio, Nebraska and Texas, are in warmer zones. The new guide, unveiled this week, also uses better weather data and offers more interactive technology. For the first time it takes into factors such as how cities are hotter than suburbs and rural areas, nearby large bodies of water, prevailing winds, and the slope of land.

The 2012 USDA Plant Hardiness Zone Map is the standard by which gardeners and growers can determine which plants are most likely to thrive at a location. The map is based on the average annual minimum winter temperature, divided into 10-degree F zones. For the first time, the map is available as an interactive GIS-based map, for which a broadband Internet connection is recommended, and as static images for those with slower Internet access. Users may also simply type in a ZIP Code and find the hardiness zone for that area.

The 26 zones, however, are based on five degree increments. In the old 1990 map, the USDA mentions 34 different US cities on its key. Eighteen of those, including Honolulu, St. Louis, Des Moines, St. Paul and Fairbanks, are in newer warmer zones. Agriculture officials said they didn’t examine the map to see how much of the map has changed for the hotter. However, the Yahoo News report said Mark Kaplan, the New York meteorologist who co-created the 1990 map and a 2003 update that the USDA didn’t use, said the latest version clearly shows warmer zones migrating north. [See the USDA Plant Hardiness Zone Map here, with zip code form, interactive mapping and downloads.]

Hardiness zones are based on the average annual extreme minimum temperature during a 30-year period in the past, not the lowest temperature that has ever occurred in the past or might occur in the future.

The USDA has said gardeners should keep that in mind when selecting plants, especially if they choose to “push” their hardiness zone by growing plants not rated for their zone. In addition, although this edition of the USDA PHZM is drawn in the most detailed scale to date, there might still be microclimates that are too small to show up on the map.

Microclimates, which are fine-scale climate variations, can be small heat islands – such as those caused by blacktop and concrete – or cool spots caused by small hills and valleys. Individual gardens also may have very localised microclimates (your entire yard could be somewhat warmer or cooler than the surrounding area, the USDA explained, because it is sheltered or exposed).

The 1990 map was based on temperatures from 1974 to 1986; the new map from 1976 to 2005. The nation’s average temperature from 1976 to 2005 was two-thirds of a degree warmer than for the old time period, according to statistics at the National Climatic Data Center. So far, according to the reports on the new zones map, the USDA is not actively associating its map with the effects of climate change on the USA.

Many species of plants gradually acquire cold hardiness in the fall when they experience shorter days and cooler temperatures. This hardiness is normally lost gradually in late winter as temperatures warm and days become longer. A bout of extremely cold weather early in the fall may injure plants even though the temperatures may not reach the average lowest temperature for your zone. Similarly, exceptionally warm weather in midwinter followed by a sharp change to seasonably cold weather may cause injury to plants as well. Such factors are not taken into account in the USDA PHZM.

David W. Wolfe, professor of plant and soil ecology in Cornell University’s Department of Horticulture said the USDA is being too cautious and has disagreed about the Agency ignoring the climate change connection. “At a time when the ‘normal’ climate has become a moving target, this revision of the hardiness zone map gives us a clear picture of the ‘new normal,’ and will be an essential tool for gardeners, farmers, and natural resource managers as they begin to cope with rapid climate change,” Wolfe has said.

Still, the USDA has emphasised that all PHZMs are guides. They are based on the average lowest temperatures, not the lowest ever. Growing plants at the extreme of the coldest zone where they are adapted means that they could experience a year with a rare, extreme cold snap that lasts just a day or two, and plants that have thrived happily for several years could be lost. Gardeners need to keep that in mind and understand that past weather records cannot be a guarantee for future variation in weather.

A warming northern hemisphere opens year 2012

The National Oceanic and Atmospheric Administration (NOAA), National Climatic Data Center global climate anomalies map for 2011 November.

The US agency, National Oceanic and Atmospheric Administration (NOAA) has through its National Climatic Data Center which monitor climate, released the 2011 November temperatures, temperature anomalies and precipitation report. This report and the accompanying charts continue the long set of readings and observations on global warming and climate change.

According to the UK Met Office, November 2011 was the second warmest November on record for the United Kingdom, Behind 1994, at 2.9°C (5.2°F) above normal. Provisionally, Scotland recorded its warmest November on record.

In Asia, China reported its third warmest November since national records began in 1951, according to the Beijing Climate Center. It was the warmest November on record in 12 provinces and second warmest in four provinces.

Cooler-than-average regions around the globe included Alaska, western Canada, much of Eastern Europe, Kazakhstan, and southwestern Russia. Alaska reported its sixth coolest November on record.

Here are the significant highlights:

* The combined global land and ocean average surface temperature for November 2011 was the 12th warmest on record at 13.35°C (55.81°F), which is 0.45°C (0.81°F) above the 20th century average of 12.9°C (55.0°F). The margin of error associated with this temperature is +/- 0.07°C (0.13°F).
* Separately, the global land surface temperature was 0.61°C (1.10°F) above the 20th century average of 5.9°C (42.6°F), making this the 16th warmest November on record. The margin of error is +/- 0.11°C (0.20°F). Warmer-than-average conditions occurred across central and eastern North America, Northern and Western Europe, northern Russia, most of China and the Middle East, southeastern Australia, and southern South America. Cooler-than-average regions included Alaska, western Canada, much of Eastern Europe, Kazakhstan, and southwestern Russia.
* The November global ocean surface temperature was 0.39°C (0.70°F) above the 20th century average of 15.8°C (60.4°F), making it the 12th warmest November on record. The margin of error is +/- 0.04°C (0.07°F). The warmth was most pronounced across the north central and northwest Pacific, the Labrador Sea, and portions of the mid-latitude Southern oceans..
* The combined global land and ocean average surface temperature for the September – November period was 0.52°C (0.94°F) above the 20th century average of 14.0°C (57.1°F), making it the 12th warmest such period on record. The margin of error is +/- 0.09°C (0.16°F.
* The September – November worldwide land surface temperature was 0.87°C (1.57°F) above the 20th century average, the seventh warmest such period on record. The margin of error is +/- 0.17°C (0.31°F).
* The global ocean surface temperature for September – November was 0.39°C (0.70°F) above the 20th century average and was the 12th warmest such period on record. The margin of error is +/- 0.04°C (0.07°F).
* The combined global land and ocean average surface temperature for the January – November period was 0.52°C (0.94°F) above the 20th century average of 14.0°C (57.2°F), making it the 11th warmest such period on record. The margin of error is +/- 0.09°C (0.16°F).
* The January – November worldwide land surface temperature was 0.84°C (1.51°F) above the 20th century average — the seventh warmest such period on record. The margin of error is +/- 0.20°C (0.36°F).
* The global ocean surface temperature for the year to date was 0.41°C (0.74°F) above the 20th century average and was the 11th warmest such period on record. The margin of error is +/- 0.04°C (0.07°F).
* La Niña conditions continued during November 2011. According to NOAA’s Climate Prediction Center, La Niña is expected to continue through the Northern Hemisphere winter 2011/12.
* The average Arctic sea ice extent during November was 11.5 percent below average, ranking as the third smallest November extent since satellite records began in 1979. The extent was 1.3 million square kilometers (502,000 square miles) below average. This marks the 18th consecutive November and 126th consecutive month with below-average Arctic sea ice extent.
* On the opposite pole, the November Antarctic monthly average extent was 0.5 percent below the 1979–2000 average, the 11th smallest on record. This is the first November since 2002 with below-average Antarctic ice extent.
* Northern Hemisphere snow cover extent was much-above average during November with the fourth largest November snow cover extent in the 46-year period of record. Both the North American and Eurasian land areas had above-average snow cover extents.
* Much of Europe experienced extreme dryness during November. Both Germany and Austria reported their driest Novembers on record. Much-wetter-than-normal conditions occurred across parts of South Asia and northeast Africa.